Credo AI vs Trustible: how they compare in 2026
Credo AI and Trustible both sell AI governance platforms that inventory an organization's AI, score its risk and produce evidence for regulators. Credo AI sits in the top two bands on nine of fifteen axes and Trustible on seven of fifteen, identical on nine. The difference is what each lets a buyer read before signing. Credo AI publishes its terms of use, which bar training on customer data and name the enterprise AI tools its own staff may use. They also carry an intellectual property indemnity, a cap of a year's fees and two warranties with stated remedies. Trustible negotiates its customer agreement privately, so none of that can be read. Its counterweight is method and disclosure about the product. Its experts normalize more than fifteen frameworks into one control library, it publishes that 72 percent of use cases are approved automatically, and it names Microsoft Azure as the host of its AI tools. Neither publishes a price or names the model behind its agents.
At a glance
All 15 axes, side by side
The same grid applied to every vendor in the index, graded from public sources. Hover a grade to see what the letter means on that axis.
AI Centrality
How much of the product is actually AI. Whether the machine learning is the mechanism the buyer is paying for or a feature layered onto conventional software, and whether the vendor is specific about which is which.
Generative capability is the engine of a core capability layered on a governance system of record that would function without it. The platform's spine is an inventory and a workflow: an AI registry with agent cards and dependency graphs, a risk and control library, policy packs mapped to named regulations, approval gates, audit trails and evidence generation. That is a system of record a customer could run with human analysts filling it in, and the vendor's own account of its history says as much, describing a 2020 to 2023 phase whose breakthrough was replacing spreadsheets and ad-hoc reviews with a policy engine. What the models add is GAIA, a set of governance agents that perform intake and registration, retrieve evidence, assess risk, draft governance plans and remediate, plus automated red-teaming, drift detection and shadow AI classification. Remove them and the registry, the policy packs and the workflows remain. Product page and Terms of Use read 7 September 2026.
Models do real work on top of a system of record that would function without them, and the vendor is unusually explicit about which half is which. The model half is genuine: the homepage shows a live governance feed in which a vendor's data processing agreement is parsed and mapped to seven ISO 42001 controls, a model provider's API is analysed and twelve risk signals surfaced, and an assistant answers natural-language questions about the AI inventory, returning named high-risk use cases with their regulatory designations. The methodology page adds that policy controls are satisfied by verifying, through AI-assisted analysis, that a customer's policy text addresses a control's guiding questions. The other half is not models and the vendor says so: the risk and regulatory intelligence layer is curated by its own policy experts and applied through what it calls a rules-based engine, framework mappings are built by experts reading each framework in full, and designations determine applicable controls by rule. Strip the models out and the inventory, the control library, the mappings, the routing and the evidence trail remain, which is the product most of this lane sells. Homepage and methodology page read 7 September 2026.
Citation Accuracy and Hallucination Disclosure
Whether the vendor publishes measured accuracy on citations and assertions, grounds output to primary sources, and says plainly what its system does when it does not know. Legal has a documented public record of fabricated citations reaching filed briefs, so an untested claim of accuracy is not evidence.
Accuracy is asserted in numbers and measured in none of them, and the agreement disclaims it outright. The product page carries 10x faster compliance, 70 per cent reduced time in engineering bottleneck, 100 per cent AI visibility and 360-degree risk coverage, none with a basis, method or test set, and a customer quote repeats the 10x figure for EU AI Act compliance. Section 8.6 of the Terms of Use states in terms that Credo AI makes no warranties or representations regarding the accuracy, reliability, timeliness or completeness of the services. Several limbs of this band do not bite and are named rather than penalised: the platform produces risk scores, control mappings and evidence artefacts rather than legal assertions citing authority, so there is no citator and no reported case to open. What does bite is the limb that matters most for a product whose output is a compliance conclusion mapped to a named statute: nothing published lets a buyer test how often GAIA's evidence retrieval or risk mapping is right, and no grounding method is described. Product page and Terms of Use read 7 September 2026.
Accuracy is asserted in numbers and measured in none of them. The site publishes framework readiness percentages, a documented count of controls a parsed agreement maps to, twelve risk signals surfaced from a vendor review, and headline claims of ten times faster intake and documentation time cut from twelve hours to two. None carries a method, a test set or an error rate. Nothing published states how often the AI-assisted analysis of a customer's policy reaches the right conclusion about whether a control is satisfied, what happens when it does not, or whether a person checks before the control is marked met. Where grounding does exist it is for the record rather than for the model's judgment: the compliance surface states that evidence is assembled from real governance activity rather than reconstructed, logged with field-level precision and timestamped to the use case, with per-article gap analysis, so a reader can trace a compliance claim to the activity behind it. Several limbs of this band do not bite and are named rather than penalised, since the outputs are control mappings and risk scores rather than legal assertions citing authority. Homepage, methodology and compliance pages read 7 September 2026.
Autonomy and Oversight Model
What the system decides on its own, what a lawyer must approve, and whether the vendor documents where the review point sits. A tool that drafts under review and a tool that files without one are different products and different risks.
A written commitment that the agents work alongside a person, with real review surfaces, short of the threshold. The product page states that GAIA's specialised agents automate the most time-consuming governance tasks while maintaining human oversight for critical decisions, and the mechanisms are named rather than gestured at: governance workflows with approval gates in the compliance module, human-in-the-loop escalation workflows in production monitoring, and human-in-the-loop escalation specifically for high-risk actions in the agentic monitoring phase. Continuous evaluation of agent traces feeds those escalations. That is more than most records on this axis publish, and it is worth crediting on a product whose own agents can run remediation. What is not published is the control structure behind it: no statement of which actions GAIA may take unattended, no threshold or criterion that defines a critical decision or a high-risk action, and nothing on what happens after a remediation agent acts wrongly. That is precisely the limb this band names as commonly absent. Product page read 7 September 2026.
The vendor publishes how much runs without a person, which most records on this axis do not, and stops short of the threshold. What is published: agentic workflows do the heavy lifting while human experts keep the customer in control; the governance agent automates tasks with context and rules while preserving human judgment where it matters; structured intake routes every use case by risk automatically; low-risk AI moves through in minutes; and the dashboard states that seventy-two per cent of use cases are auto-approved with an average review time of 1.8 days. Publishing the auto-approval rate is a real disclosure of the boundary rather than a claim about oversight. The review surfaces are named alongside: a task queue with review types and statuses, reviews routed to the right stakeholders, and an agentic activity feed showing what was triaged, analysed, parsed and reassessed with timestamps. What is missing is the limb this band names as commonly absent: nothing defines what counts as low risk, no threshold or criterion is published for the auto-approval path, and nothing states what happens when a use case was auto-approved and should not have been. Homepage and platform description read 7 September 2026.
Operational and Outcome Evidence
Named, dated evidence that the product works in production at real firms or legal departments. Case studies with figures and identified customers count. Unattributed testimonials and launch announcements do not.
Named customers with named people, short of dates and method. The product page carries attributed statements from Andrew Reiskind, Chief Data Officer at Mastercard, on managing AI risk and implementing generative AI at speed and scale using the AI Registry and Vendor Registry; Renee Langeness, Director of Data Governance at Principal, on standing up an enterprise AI governance workflow; Parth Patel, Executive Director for AI and Data Science, on complementing internal processes; Kathleen Cachel, Senior Data Scientist at AdeptID, on centralised support for annual technical audits; and Brad Mallard, a CTO, on using the platform internally for compliance with its own policies and the EU AI Act. Partner statements from Microsoft's Chief Product Officer for Responsible AI and IBM add substance about what the integration does. One figure appears inside a customer quote, compliance with the EU AI Act at ten times the speed of doing it manually, with no method attached, and the page's own counters carry no basis. No deployment is dated. The customers and case studies page was not read and is the route to more. Product page read 7 September 2026.
Named customers with named people in named roles, and figures that float free of them. Three customer stories are published with attributed quotations: Leidos, where a VP of AI Strategy and Governance says the platform turbocharged use case throughput across a programme spanning forty countries; Nuix, where the General Counsel says AI governance became an operational reality that is evidence based; and Ashoka, where a Vice President for Global Integrity describes a small team doing work of a much larger one. The wider roster names Guardian Life, Boston Scientific, Molson Coors, Olympus, Korn Ferry, Evertec, Kroll, Databricks and Google. The figures are separate from the names and carry no method: ten times faster intake, four times more use cases approved, sixty per cent reduction in cycle times, seventy-two per cent auto-approved, 1.8 days average review, and documentation time cut from twelve hours to two. A third-party account of a Leidos proof of concept describes intake compressed from weeks to hours or minutes and is described rather than credited. Homepage, SOC 2 announcement and case study listings read 7 September 2026.
Privilege and Confidentiality Posture
How client confidences are handled: attorney client privilege and work product treatment, segregation of one client matter from another, whether client data trains any model, and what the vendor commits to in writing rather than in marketing.
Substantive published commitments, including one that is unusually specific, short of segregation and of a limb the agreement itself complicates. What is committed: section 6.8 of the Terms of Use bars Credo AI from using, processing or otherwise accessing User Data to train, develop or improve any machine learning or artificial intelligence model, and confines its access to providing, maintaining and supporting the service; the same clause names the enterprise AI tools Credo AI's staff may use to deliver the service, states that use is confined to Credo AI's own enterprise environment and team members, that no user data leaves it, and that such data is deleted at the end of the engagement. Section 11.3 makes User Content the customer's Confidential Information, 11.4 limits disclosure to those with a need to know under equivalent obligations, and 6.6 sets a sixty-day post-termination window followed by deletion. Two things hold it here. Nothing published addresses segregation between customers or between teams inside a tenant. And section 5.2 grants Credo AI a worldwide, sublicensable, transferable licence to use, reproduce, modify, adapt, publish, translate, create derivative works from, distribute, perform and display User Content in connection with providing and improving the services: the purpose limitation is narrow but the verbs are not, and a governance platform holds a customer's AI risk assessments and incident records. Terms of Use read in full 7 September 2026.
Confidentiality is asserted in general terms and no commitment a buyer could read before signing was located. The customer agreement is not published: the terms of service state that services are provided under separate agreements negotiated individually with each customer, so there is no published confidentiality clause, no statement of who at the vendor may access customer content, and no segregation position. What does exist is narrower than this axis needs and is credited where it belongs rather than here: the privacy policy commits that the AI tools are not trained on Personal Information and do not retain Personal Information uploaded into them, and the SOC 2 Type II covers data and privacy controls among its five areas. Both are expressed as to Personal Information rather than to the governance content a customer loads, which for this product is use case descriptions, vendor contracts, policy text and completed assessments. Nothing addresses segregation between customers, nothing states what the model host may retain, and the security section of the privacy policy is expressly hedged, promising reasonable efforts and no guarantees. Terms of service, privacy policy and SOC 2 announcement read 7 September 2026.
UPL and Professional Responsibility Posture
Whether the vendor is clear that it supplies a tool rather than legal advice, who its audience is, and how it addresses unauthorized practice of law, competence and supervision duties, and jurisdiction limits. ABA Formal Opinion 512 is the reference point. Where the advice line is not the duty a product raises, the axis is read through the nearest professional duty it does raise: judicial conduct rules and the reviewing duty for products sold only to courts, and the duty to bill for time actually spent for products that draft time entries.
A boilerplate disclaimer sits in the terms while the marketing describes regulatory conclusions, and nothing addresses where the output stops and a legal judgement begins. The product is sold on full alignment with European AI regulation including risk classification and conformity assessments, complete NIST Risk Management Framework compliance, and audit-ready documentation for every major AI regulation. Classifying a system's risk tier under the EU AI Act is a legal characterisation with consequences, and the company also sells advisory services described as strategic advisory related to AI governance. The counterweight located is section 8.6, disclaiming any representation as to accuracy, reliability, timeliness or completeness, which is a warranty disclaimer rather than a statement about advice. Nothing published says that a policy pack mapping, a risk classification or a conformity artefact is not legal advice, that counsel remains responsible for the determination, or which jurisdictions the regulatory content is maintained for. The audience is unambiguous and professional, which is recorded rather than credited. Same grade and same reasoning as the comparable records in this lane. Terms of Use and product page read 7 September 2026.
A boilerplate disclaimer sits in the website terms while the product produces regulatory characterisations, and nothing addresses where its output stops and a legal judgement begins. The characterisations are specific and consequential: designations of High Risk, Provider, Deployer and GPAI determine which EU AI Act obligations attach to a customer's system, per-article gap analysis reports where a programme falls short of named articles, and the assistant will tell a user which of its use cases qualify as high-risk AI systems under the Act. Those are legal conclusions in substance. Nothing published states that they are not legal advice, that counsel remains responsible for the classification, or what jurisdictional limits apply to the framework content. The only disclaimer language located is in the website terms of service, which govern the site rather than the platform, and the customer agreement that might address it is not published. Same grade and reasoning as the comparable records in this lane. Homepage, methodology page and terms of service read 7 September 2026.
AI Governance and Bias Disclosure
Published governance over model behavior: who owns it inside the vendor, what is tested before release, and what is disclosed about disparate output across matter types, parties, or populations.
Principles and a commitment are published; a governance framework for the vendor's own AI is not. Credo AI publishes an ethos page, runs an annual AI trust summit, maintains a public governance insights hub and glossary, and positions itself as the company that pioneered the category, so responsible AI language is abundant. One commitment goes further than language and is credited here as real substance: section 6.8 of the Terms of Use is a binding statement about how Credo AI handles customer data in relation to AI models, including which enterprise AI tools its own staff may use. What is still absent is the governance half. Nothing published names who inside Credo AI is accountable for GAIA's behaviour, describes what is evaluated before a governance agent ships, reports any result from such evaluation, or discloses anything about uneven output across sectors, jurisdictions or populations. The company sells ISO 42001 policy packs and does not claim the certification for itself, and the trust centre that might carry more returns no body on this channel and is named as the rebuttal route. Terms of Use, product page and trust centre attempted 7 September 2026.
A principle is published and no mechanism stands behind it, which is worth stating precisely because of what this company sells. The principle is explicit: in its own SOC 2 announcement the chief executive says governance is the product, so the company holds itself to the same standard it asks its customers to meet, and it is constituted as a Public Benefit Corporation. Tested against the published record, the claim holds on security and not on AI. On security there is a third consecutive SOC 2 Type II with five named audit areas. On its own AI there is nothing comparable: nobody is named as accountable for the governance agent's behaviour, no evaluation before release is described, no result from any such evaluation is published, no bias or reliability disclosure exists for the AI-assisted policy analysis that decides whether a control is met, and the company claims no ISO 42001 certification of its own while selling ISO 42001 readiness to others. It does publish model ratings for third-party generative systems at a separate site, which is a product capability rather than governance of itself. The trust centre could not be read on this channel and is the rebuttal route. SOC 2 announcement, homepage and methodology page read 7 September 2026.
AI Safety and Data Stewardship
Retention, deletion, access control, and what happens to prompts and documents after they are processed. Whether the vendor states its subprocessors and its incident practice, or leaves the buyer to assume.
Substantive published policy across most of the ground, short of the security detail and the subprocessor list. What is published in the Terms of Use: retention and deletion are specific, with User Data retained as long as needed to provide the services, a sixty-day post-termination window for export using standard export features, and deletion after it (6.6); access is confined by 6.8 to providing, maintaining and supporting the service, with the enterprise AI tools used by staff named and their data deleted at the end of the engagement; incident practice is stated, with notice without undue delay after becoming aware, reasonable steps to mitigate and minimise damage, and an express statement that notification is not an admission of fault (6.9); aggregated and anonymised use is permitted but conditioned on non-attribution (6.7); and confidential information must be returned or destroyed on request with written certification (11.7). What is missing is the specificity the top band needs. Security is described only as reasonable administrative, technical and physical safeguards, with no encryption standard, access control, testing regime or logging commitment; no subprocessor list was located; and the data processing agreement is provided on request rather than published. The Vanta-hosted trust centre would be the route to the security detail and returns no body on this channel. Terms of Use read in full 7 September 2026.
Substantive published policy across most of the ground, short of incident practice and access control. What is published: a third consecutive SOC 2 Type II certification whose five audit areas are named, including data and privacy controls, tested for operating effectiveness over a period rather than design at a point in time; four subprocessors identified by name in the privacy policy, being Amazon Web Services, Microsoft Azure, Cloudflare and PostHog; hosting stated to be in the United States with Standard Contractual Clauses for European transfers; a retention approach that commits to deleting or de-identifying personal information when it is no longer necessary, with the criteria for setting the period described; and an explicit statement that the AI tools do not retain Personal Information uploaded into them. Two limbs are missing and one is hedged: no incident or breach notification practice is published anywhere, no access control or personnel restriction is described, and the security section promises reasonable efforts with an express disclaimer that no guarantee is given. The trust centre states it carries a controls breakdown and a hosting FAQ, and returned no body on this channel, which is recorded as a retrieval limit rather than an absence. Privacy policy and SOC 2 announcement read 7 September 2026.
AI Liability and Recourse
What the vendor stands behind contractually when its output is wrong. Indemnities, caps, carve outs, insurance, and whether any of it is published or only reachable through a negotiated agreement.
What the vendor stands behind is published and specific, including the places where it stands behind nothing. Section 10.1 of the Terms of Use gives a defence and indemnity against third-party claims that the services infringe or misappropriate intellectual property rights, with six named exclusions at 10.2 and the mitigation ladder at 10.3 of obtaining the right, modifying or replacing the services with substantially equivalent functionality, or terminating with a pro-rated refund. Section 9.2 caps each party's aggregate liability at the total paid in the twelve months preceding the incident, and 9.3 lifts the cap and the exclusion of indirect damages for breach of confidentiality and for the customer's breach of the licence and acceptable use terms. Two express warranties carry stated remedies: the SaaS products will perform materially in accordance with the documentation, remedied by correction or termination with a pro-rated refund (8.4), and advisory services will be performed in a professional and workmanlike manner, remedied by re-performance or refund (8.5), each declared the exclusive remedy. Section 8.6 disclaims everything else and states plainly that no representation is made about the accuracy, reliability, timeliness or completeness of the services, and 14.1 gives a termination right with a pro-rated refund if a change materially reduces functionality. No insurance is stated, the indemnity is not carved out of the cap, and the service level agreement is referred to as mutually agreed rather than published. Terms of Use read in full 7 September 2026.
Nothing published states who bears the loss when the product is wrong, and the vendor says why. The terms of service of 3 October 2025 govern the website and state that the services are provided under separate agreements negotiated on an individual basis with each customer. So there is no published indemnity, no liability cap, no warranty, no service level commitment, no exclusive remedy and no insurance statement, and none was located on any other surface. This is recorded as a disclosure choice rather than an accusation: the vendor discloses that the agreement exists and is negotiated privately, which is more than the two records in this lane that publish website terms and leave a reader to infer the rest. The exposure a buyer cannot price is worth naming on a product of this kind: the platform produces the regulatory classifications and evidence packages an organisation would rely on in front of a regulator, and nothing published says what the vendor stands behind if a classification or an evidence package is wrong. Terms of service and all located surfaces checked 7 September 2026.
Practice Systems Integration Depth
How deeply the product reaches into the systems legal work already lives in: document management such as iManage and NetDocuments, Word and Outlook, contract lifecycle management, matter management, e-billing, and court filing systems.
Named integrations across the systems the work actually lives in, short of an implementer's description. The product page lists them by category: cloud and AI operations with AWS, Azure, GCP, Databricks and Snowflake; agent platforms with Azure AI Foundry, LangChain, CrewAI and AutoGen; governance, risk and security with ServiceNow, Archer, OneTrust and Qualys; development and MLOps with GitHub, MLflow, Jira, Confluence and Slack; and custom APIs, webhooks, SDKs and connectors, with a separate SDK documentation site and a stated ecosystem of more than thirty partners. One integration is described in enough detail to see what moves, and by the counterparty: Microsoft's Chief Product Officer for Responsible AI states that it delivers prescriptive guidance to governance leaders on what to evaluate and lets developers run governance-aligned evaluations inside their own workflow. The registry also governs MCP servers and platform connections. What is not published on the page read is per-integration depth, direction or configuration; the SDK documentation was not read and is not credited by its title. Product page read 7 September 2026.
An integration surface is described and no integrations are named. The platform plainly ingests from outside itself: the governance feed shows a third-party data processing agreement parsed and mapped to controls and a model provider's API analysed for risk signals, the implementation plan commits to connecting the customer's systems in the first thirty days, and the product is positioned as a system of record that vendor and model reviews feed into. What is absent is any named connector, any statement of what moves in which direction, and any documentation an implementer could work from. No integration list, no API or SDK documentation and no partner directory was located on the surfaces read. Two things are recorded so the grade is read correctly: a third-party assessment describes the platform as operating on metadata rather than in the data path, which is described and not credited; and the two site pages most likely to carry an integration list, the platform overview and the agentic governance feature page, both returned 404 despite appearing in the site's own navigation on every page, which is a site fault rather than a limit of this channel. Homepage, methodology page and navigation checked 7 September 2026.
Deployment Model and Data Residency
Where the software runs and where the data sits. Multi tenant cloud, single tenant, private deployment, on premises, and whether region of residence is a published option or an enterprise conversation.
Nothing published on where the software runs or where customer data sits was located on any readable surface. The Terms of Use describe SaaS products accessed through a browser or API and say nothing about hosting region, data residency, tenancy or a deployment choice; the product page describes architecture in functional layers rather than infrastructure; no region selector, residency commitment or single-tenant option appears anywhere read. Two things are recorded so this reads as what it is. First, the vendor's trust centre at trust.credo.ai is a Vanta-hosted portal that returns page metadata with no body on this channel, so the surface most likely to carry hosting and residency detail could not be read; that is a retrieval limit under the standing convention, it is named here as the rebuttal route, and it would move this grade on a read. Second, the agreement does disclose one adjacent fact, at 15.9, that the services may be subject to United States and other export laws, which places the vendor in the US but is not a residency statement. This grade records what is establishable on the date. Terms of Use and product page read, trust centre attempted, 7 September 2026.
One region is stated and the deployment model is not. The privacy policy says the services are hosted in the United States and are intended for visitors located within the United States, that using them from Europe or elsewhere means transferring personal information to the United States for storage and processing, and that European transfers rely on European Commission or United Kingdom approved Standard Contractual Clauses. It separately states that the AI tools are hosted through Microsoft Azure, and names Amazon Web Services and Microsoft Azure among the subprocessors, so a buyer can establish the country and the cloud providers. Nothing goes further: no region selection, no European or other non-US hosting option, no tenancy model, no single-tenant or self-hosted arrangement, and no statement addressing where processing happens as distinct from where data is stored beyond the transfer mechanism. The trust centre states it contains a FAQ on how customer data is hosted and secured, which is where the rest would sit, and returned no body on this channel. Privacy policy and SOC 2 announcement read, trust centre attempted, 7 September 2026.
Security Certifications and Trust Center
Independent attestation a buyer can pull without a sales call: SOC 2, ISO 27001, penetration test summaries, a trust center with current reports and named scope rather than a badge image.
A certification is named by the vendor and no scope, date or reachable report was located. The trust centre at trust.credo.ai states, in the vendor's own words, that Credo AI maintains a SOC 2 Type II examination and invests continuously in its security program so that the platform its customers rely on meets the same governance standards it helps them achieve. The platform's own compliance module lists SOC 2 among the frameworks it supports for customers, which is a product capability and is not counted here. What is missing is everything that would make the attestation checkable: no auditor, no examination period, no report date, no scope statement, and no route to the report that could be established, since the trust centre is a Vanta-hosted portal returning page metadata with no body on this channel. That is recorded as a retrieval limit rather than as an absence, the portal is the rebuttal route, and the lower tier is graded with the reason stated. Trust centre attempted and Terms of Use read 7 September 2026.
The most substantive certification disclosure in this lane, short of a report a reader can reach. What is published, in the vendor's own announcement of 18 August 2026: a renewed SOC 2 Type II certification, stated to be the third consecutive one, so the controls have held across multiple audit cycles; an explanation of what Type II means, testing whether controls operated effectively over an extended period rather than were designed well at a point in time; and the five areas this cycle's audit examined, being infrastructure security controls, organisational security controls, product security controls, internal security procedures, and data and privacy controls. A trust centre was launched alongside it, stated to carry a compliance overview, a full breakdown of controls by category, a subprocessor list, and a FAQ on how customer data is hosted and secured. What keeps this off the top grade is reachability and specificity: no auditor is named, no report period or date is given, no scope statement identifies the product or entity covered, and the report itself is available on request for customers and prospects conducting vendor due diligence rather than self-serve. The trust centre returned page metadata with no body on this channel, so its contents could not be verified. SOC 2 announcement read in full and trust centre attempted 7 September 2026.
Model Supply Chain Disclosure
Which models sit underneath, whose they are, where they run, and whether the vendor commits to telling customers when that changes. A legal buyer inherits every dependency it cannot see.
The vendor describes a proprietary intelligence layer and governance agents without identifying what sits underneath them. GAIA is presented as a set of AI agents performing evidence retrieval, risk assessment, incident response and remediation, powered by what the product page calls a proprietary governance knowledge graph; no model, provider, hosting location or change-notification commitment for those agents was located anywhere. Two adjacent facts are deliberately not credited here, because each belongs to a different arrow. The models named on the site, ChatGPT, Claude and Gemini, are the customer's deployments that the product governs through generative AI guardrails, not Credo AI's supply chain. And the enterprise AI tools named in clause 6.8 of the Terms of Use are the tools Credo AI's own staff use to support the service, which is a statement about internal operations and is credited on the training and confidentiality rows instead. No subprocessor list was located. The trust centre is the likely route to a supply chain disclosure and returns no body on this channel. Product page, Terms of Use and trust centre attempted 7 September 2026.
The supply chain is partly disclosed: a host is named, the models are not. The privacy policy states that the AI tools are hosted through Microsoft Azure, and lists four subprocessors by name, being Amazon Web Services, Microsoft Azure, Cloudflare and PostHog, with hosting stated to be in the United States. That answers where the AI runs and which providers are in the path, which is more than most records in this lane offer. Three things are absent. No model or model family is named, and under the standing rule naming a provider is not naming a model, so the top grade is unavailable. No commitment is given to notify customers when the arrangement changes. And nothing distinguishes which parts of the platform route customer content to the Azure-hosted tools. One arrow is deliberately not crossed: Anthropic and OpenAI appear on the homepage only as the vendors being governed in a demonstration, a Claude API vendor review and an OpenAI data processing agreement being parsed, so they belong to the customer's estate rather than to Trustible's own stack. Privacy policy and homepage read 7 September 2026.
Commercial Transparency
Whether a buyer can learn what this costs without entering a sales process: published rates, the unit being charged, what sits behind an enterprise tier, and what implementation adds.
The shape is partly visible and no number is published at any level. There is no pricing page; every path ends at Talk to an Expert or a personalised demo, offered without a credit card. What a buyer can see before that conversation is the modular structure, which the vendor makes a selling point: AI Registry and Discovery, Risk Intelligence, Compliance and Policy Engine, and Governance are named as modules that work independently, with the advice to land with the registry and add the others as adoption grows, alongside separately sold advisory services. The Terms of Use add the mechanics: fees are set in an order form or statement of work, based on services purchased rather than actual usage, non-cancellable and non-refundable, invoiced in advance and payable within thirty days, with 1.5 per cent monthly interest on late amounts, automatic renewal unless either party gives thirty days' notice, and price changes effective at renewal on reasonable prior notice. Section 3.4 confirms account tiers exist with varying features and usage limitations, and 4.3 warns that exceeding them may incur charges at then-current rates, though neither the tiers nor the limits are named publicly. No VendorPricing row is written, since a row belongs to vendors graded A or B on this axis. Terms of Use and product page read 7 September 2026.
No pricing information is published at any level, including the unit of charge. There is no pricing page, and none appears in the site navigation, which carries platform, solutions, company and resources sections and ends every path at a demo request. No tier or edition is named, no unit is identified, whether by use case, seat, model, framework or enterprise, no band or range appears, and no minimum or term is stated. The customer agreement that would carry the commercial mechanics is not published, since the terms of service state that services are provided under separately negotiated agreements. The only adjacent commercial fact located is the implementation shape rather than its price: a thirty, sixty and ninety day plan with a named advisor and hands-on enablement, which tells a buyer that professional services are part of the engagement without saying what any of it costs. No VendorPricing row is written. Site navigation, terms of service and homepage checked 7 September 2026.
Firm and Practice Coverage
Who the product is actually built for. AmLaw, midlaw, small firm and solo, in house departments, government and courts, and which practice areas are supported rather than merely claimed.
Coverage is described with substance across buyers and regulations, and the boundaries are left open. The platform architecture names five stakeholder types it connects, the governance lead, the business user, product and engineering, legal and compliance, and information security and third-party risk management, which is a published account of who sits in the workflow. Regulatory coverage is named rather than gestured at, with pre-built policy packs for the EU AI Act, the NIST AI Risk Management Framework, ISO 42001 and SOC 2, and the knowledge graph described as distinguishing a model used in EU healthcare from one used in US financial services. The customer evidence spans payments, insurance, professional services and a technology vendor, and the vendor states Fortune 500 adoption. What is not stated is any limit: no jurisdiction, regulation, sector or organisation size is named as out of scope, no coverage boundary is given for the regulatory content, and nothing describes what a law firm rather than an in-house function would do with the platform. Product page read 7 September 2026.
Coverage is described with real substance on the regulatory side and the boundaries are left open. Fifteen frameworks are published individually, each with its jurisdiction and its type stated, and the vendor distinguishes binding regulation from certifiable standard from voluntary framework rather than listing them flat: the EU AI Act, Colorado's AI Act, the Connecticut bill, NYDFS guidance, the NAIC model bulletin, Colorado insurance regulation, OMB M-25-21, the GAO framework, a financial services risk management framework, ISO/IEC 42001, the NIST AI RMF, the Singapore framework, the Australian government standard, the CHAI healthcare guidelines and South Korea's AI Basic Act. Scope within a customer is defined by designations, so High Risk, Provider, Deployer and GPAI determine which controls apply to each system. Four industries have their own surfaces, being financial services, healthcare, insurance and technology, and the customer roster adds defence and nonprofit. The buyer is described as governance teams, with the trust centre stating the platform is built for enterprise AI and legal teams. What is not stated is any limit: no jurisdiction, sector or organisation size is named as out of scope, and no coverage depth is given for frameworks outside the three the site treats in detail. Methodology page, homepage and trust centre metadata read 7 September 2026.
The 12 legal signals, side by side
Recorded rather than graded. These are the questions a practitioner has to answer before a tool touches a client matter, and the answers are taken from public material only.
Client Data in Training
Can material a lawyer puts into this product be used to train a model?
The published agreement prohibits training, in the agreement rather than on a policy page. Section 6.8 of the Terms of Use, effective 21 April 2026, states that Credo AI will not use, process or otherwise access User Data to train, develop or improve any machine learning or artificial intelligence models, and that its access to User Data is solely to provide, maintain and support the services. The same clause discloses something no other record in this index carries: it names the enterprise AI tools Credo AI's own staff use in delivering the service, including ChatGPT Enterprise and custom GPTs, Gemini Enterprise, Claude Enterprise and Microsoft Copilot, and commits that such use stays inside Credo AI's enterprise account environment and team, that no User Data leaves that environment, and that the data is deleted at the end of the engagement.
Two qualifiers travel with the value and are recorded rather than smoothed over. Section 5.2 grants a broad content license over User Content, including rights to modify, publish, distribute and create derivative works, scoped to providing and improving the services. And section 6.7 permits Credo AI to use aggregated and anonymized data derived from use of the services for its own business purposes, including developing new products, provided it cannot be attributed to the customer. Neither displaces 6.8, which is the specific clause and names the thing. Terms of Use read in full 7 September 2026.
Public material states that customer content does not train the models, and no agreement is published to match it. Section 6 of the privacy policy, last updated 3 October 2025, is headed How We Use Artificial Intelligence and says the customer may interact with AI while using the services, that the AI tools are hosted through Microsoft Azure, and that Trustible does not train its AI tools with the customer's Personal Information.
The value's own text requires that no matching term be located in a published agreement, and the search for one was completed rather than assumed: the terms of service govern the website and state that the services are provided under separate agreements negotiated on an individual basis with each customer, so there is no published contract to check against. Two scope limits travel with the commitment and are recorded rather than smoothed over.
It is expressed as to Personal Information, not to customer content generally, and the material this platform holds is largely not personal data: use case descriptions, vendor contracts, policy text and completed assessments. And it is expressed as to the AI tools, leaving the platform's other processing unaddressed; the policy separately reserves use of information to develop new products, services and features. Privacy policy and terms of service read 7 September 2026.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
A specific period is published for the end of the relationship and the customer cannot change it. Section 6.6 of the Terms of Use sets a sixty-day window after termination or expiry during which the customer may export using standard export features, after which Credo AI may delete User Data except as required by law or for its legitimate business purposes, and it recommends regular customer-side backups. Two limits on that are stated here so the row is not read as more than it is.
In-term retention is not a period at all but a standard, User Data kept as long as needed to provide the services and to meet legal, dispute and enforcement needs, so a customer cannot read off how long a GAIA prompt or a generated governance artifact persists while the subscription runs. And no zero-retention or customer-configurable window is offered anywhere located. Section 6.7 separately permits indefinite use of aggregated and anonymized derivatives.
A reader could hold the vaguer value on the in-term half; the specific published period is what the value records. Terms of Use read in full 7 September 2026.
A published position the customer cannot change, and it is the strongest form of one: no retention at all by the AI tools. Section 6 of the privacy policy states that the AI tools do not retain Personal Information uploaded into them. That is a vendor default rather than a customer setting, which is why this sits at the fixed value rather than a configurable one, and no option to vary it is offered. The same two scope limits as on the training row apply and matter more here.
The commitment covers Personal Information rather than the governance content that makes up most of what a customer loads, and it covers the AI tools rather than the platform, which is a system of record designed to keep assessments, decisions and evidence indefinitely so they can be produced to an auditor. For the platform's own records the policy gives criteria rather than a period, committing to delete or de-identify personal information when it is no longer necessary and listing the factors that set the period. Privacy policy read in full 7 September 2026.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
No located public material addresses segregation between users, teams or customers. The Terms of Use put administrative users in charge of managing access levels and permissions for their organization at 3.3, which is a customer-side control over its own people rather than a statement about how the platform separates one organization's governance records from another's, or whether a business user registering an AI system can see assessments belonging to a different part of the enterprise.
The product page describes connecting every stakeholder to every AI system, which is the opposite emphasis. Nothing read describes tenancy, isolation or permission enforcement at retrieval time, including for GAIA's evidence retrieval across a customer's records. The trust center would be the likely route and returns no body on this channel. Terms of Use and product page checked 7 September 2026.
No located public material addresses segregation between customers or inside a customer's own tenant. The platform is built around shared visibility rather than compartmentation, routing use cases to reviewers across risk, legal, compliance and business teams and giving leadership a live dashboard view, and nothing published describes whether a reviewer in one business unit can see assessments belonging to another, or how one organization's inventory, vendor reviews and policy analysis are isolated from another's. No customer agreement is published that would carry a confidentiality or segregation term, and the trust center that states it holds a controls breakdown returned no body on this channel. Methodology page, homepage, privacy policy and terms of service checked 7 September 2026.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
The agreement commits to prior written notice where legally permitted, with minimization. Section 11.6 of the Terms of Use permits disclosure of confidential information to the extent required by law, regulation or court order only on condition that the receiving party gives prior written notice so the disclosing party may seek a protective order or other appropriate remedy, and discloses only the portion legally required; if no protective order is obtained, it must furnish only what is legally required and use commercially reasonable efforts to obtain assurance of confidential treatment.
Section 11.3 makes User Content the customer's confidential information, so the clause reaches the governance records and assessments a customer holds in the platform rather than only account data. No transparency report, request statistics or law-enforcement guidelines page was located, which is what separates this from the top value, and there is no separate law-enforcement protocol of the kind some records in this pull carry. Terms of Use read in full 7 September 2026.
Disclosure to authorities is addressed and customer notice is not. The privacy policy's disclosure section states that Trustible may access, preserve and disclose Personal Information where it believes doing so is required or appropriate to comply with law enforcement requests and legal process such as a court order or subpoena, to respond to requests, or to protect rights, property or safety. It carries no commitment to notify the customer, no reservation of discretion over notice, no undertaking to seek a protective order, and no limit to the portion legally required.
The threshold is also broad on its own terms, extending to what the vendor believes appropriate rather than only what is required. No compelled-disclosure clause exists to supplement it, because the customer agreement is not published, and no transparency report or law enforcement guidelines page was located. Privacy policy read in full and terms of service checked 7 September 2026.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
The sources behind the product's compliance content are identified by name and no license or rights basis is stated for any of them. The compliance and policy engine ships pre-built policy packs for the EU AI Act, the NIST AI Risk Management Framework, ISO 42001 and SOC 2, and the governance knowledge graph is described as connecting regulations, risks, controls and business context into a proprietary intelligence layer, with a separately published regulatory insights hub and risk and control library.
So a buyer can see which instruments the content derives from, which is more than the signal's lowest value describes. What is absent is the rest: no statement of the license or rights basis for the standards content, which matters because ISO 42001 and the SOC 2 trust services criteria are copyrighted works rather than public law; no update cadence for the packs as regulations change, in a domain where the EU framework has been amended; and no statement of jurisdictional coverage depth. Product page and Terms of Use read 7 September 2026.
The sources are named individually and the maintenance is described, with no license basis stated. Fifteen frameworks are published with their jurisdiction and type, so a buyer can see exactly which instruments the control library derives from, and the derivation itself is unusually well described: policy and regulatory experts read each framework in full, identify every obligation and clause, normalize them into Controls, and map each Control to every article it satisfies.
Currency is addressed rather than assumed, with experts stated to monitor framework changes continuously and update mappings so a customer's completed work carries forward, which is more than most records on this signal offer. What is absent is the rights basis. Several of the sources are copyrighted works rather than public law, ISO/IEC 42001 among them, and nothing states the license under which their requirements are reproduced or normalized into the product.
Nothing states when each mapping was last reviewed, or what a customer sees if an assessment was completed against a superseded version. Methodology page read in full 7 September 2026.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
No located public material addresses whether the authority behind the product's outputs is checked for currency. The signal's ordinary subject, subsequent history of reported cases, does not bite for a platform whose outputs are risk classifications and control mappings rather than citations to case law, and that is recorded rather than penalized. The analog that would bite is whether the policy packs and control library track amendments to the instruments they encode, and nothing read commits to it: the vendor publishes regulatory intelligence and an explainer on changes to the EU framework, which shows the content is being maintained, but no statement describes how a customer learns that a pack has changed, when it was last aligned, or what happens to an assessment completed under a superseded version. Product page, Terms of Use and regulatory materials checked 7 September 2026.
No located public material addresses whether authority is checked for subsequent history, and the limbs do not bite for this product class. The outputs are control mappings, designations, risk scores and evidence packages rather than citations to case law, so there is no reported decision whose treatment a user would need to check. The analog that does bite, whether the framework mappings track amendments to the instruments they encode, is addressed on this record and is credited on the corpus provenance row rather than counted twice here: the vendor describes continuous monitoring of framework changes by its own experts, with mappings updated as regulations and standards evolve.
What is still missing there, and worth naming once, is any statement of when a given mapping was last reviewed. Methodology page and homepage checked 7 September 2026.
Refusal and Uncertainty Behavior
What does the product do when the answer is not in the corpus?
No located public material describes what the governance agents do when they cannot ground an answer. The published material addresses oversight rather than uncertainty: human oversight is maintained for critical decisions, workflows carry approval gates, and high-risk actions escalate to a person. Those are controls over what an agent is allowed to finish, not a description of what it does when the evidence it needs is missing or ambiguous.
Nothing read exposes a confidence or grounding score, describes an abstention path for GAIA's evidence retrieval or risk assessment, or reports any evaluation in which the system declined. The distinction matters on a product whose agents draft governance plans and remediate incidents. Product page and Terms of Use checked 7 September 2026.
No located public material describes what the assistant or the governance agent does when it cannot reach a supported answer. The published material addresses authority rather than uncertainty: agents automate tasks with context and rules while preserving human judgment where it matters, and low-risk work is auto-approved while higher-risk work routes to reviewers. Those describe who decides what, not what the system does when the evidence is thin.
Nothing states whether the assistant declines a question it cannot ground in the inventory, whether the AI-assisted policy analysis reports that it could not determine whether a control is satisfied rather than guessing, or whether any confidence or coverage signal is exposed to the reviewer. That matters on this product because the analysis decides whether a control is marked met, and a control marked met on a wrong reading becomes evidence produced to an auditor. Homepage, methodology page and privacy policy checked 7 September 2026.
Fabricated Citation Record
Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?
No court order, opinion or disciplinary record naming Credo AI or GAIA was located as of 7 September 2026. The AI Hallucination Cases database maintained by Damien Charlotin was searched on both names alongside a general search of the sanctions coverage; the decisions naming specific tools name general-purpose chatbots and legal research products. This is a statement about the public record, not a finding about the product.
Exposure is structurally remote for a platform whose outputs are internal governance artifacts rather than filings, though the artifacts it generates are designed to be shown to regulators and auditors, which is a different audience carrying its own accuracy expectations.
No court order, opinion or disciplinary record naming Trustible or Trible AI was located as of 7 September 2026. The AI Hallucination Cases database maintained by Damien Charlotin was searched on the company name alongside a general search of the sanctions coverage; the decisions naming specific tools name general-purpose chatbots and legal research products. This is a statement about the public record, not a finding about the product.
Exposure is structurally remote for a platform whose outputs are internal governance artifacts rather than filings, with the qualification that those artifacts are built to be produced to regulators and auditors, an audience that carries its own accuracy expectations even though it is not a court.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
No located public material engages with bar or ethics guidance, or with lawyers' professional obligations in general terms. Credo AI engages regulation heavily and at a high level of specificity, publishing policy packs, a regulatory insights hub, an explainer on changes to the EU AI framework and an annual trust summit, and it names legal and compliance as a stakeholder group in the platform. All of that concerns the obligations of the organizations that buy the product.
Nothing names an ethics opinion, a bar association guidance document or a regulator's guidance on lawyers' use of AI, and nothing addresses the duties of a lawyer relying on a governance artifact the platform generated. The lower value was tested before this one was taken: a generic reference would need some engagement with professional responsibility as such, and none was located. Product page, Terms of Use, legal pages and resource listings checked 7 September 2026.
No located public material engages with bar or ethics guidance, or with lawyers' professional obligations in general terms. Trustible engages regulation in more depth than most records in this lane, publishing fifteen frameworks with their obligations normalized into controls, and it addresses legal teams as a buyer, with its trust center describing the platform as built for enterprise AI and legal teams and a General Counsel appearing as a named customer voice.
All of that concerns the obligations of the organizations that buy the product. Nothing names an ethics opinion, a bar association guidance document or a regulator's guidance on lawyers' use of AI, and nothing addresses the position of in-house counsel who signs off a regulatory classification the platform generated. The lower value was tested before this one was taken: a generic reference would require some engagement with professional responsibility as such, and none was located. Methodology page, homepage, privacy policy and terms of service checked 7 September 2026.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
The product does not touch a fee between a lawyer and a client. Credo AI is licensed by an enterprise to govern its own AI systems, and the stakeholders named in the platform are governance leads, business users, engineering, legal and compliance, and information security, all of them internal functions that bill no client for the work. The efficiency claims on the product page, ten times faster compliance and seventy percent less time in engineering bottlenecks, are aimed at the buyer's own cost and cycle time, which the value text records as not making the row a savings claim.
Advisory services are sold alongside the platform but are Credo AI's own consulting engagement rather than a lawyer-to-client matter. Nothing addresses billing, fee or disclosure treatment because there is no client invoice for it to address. Product page and Terms of Use checked 7 September 2026.
The product does not touch a fee between a lawyer and a client. Trustible is licensed by an enterprise to govern its own AI estate, and the users it names are governance leads and cross-functional reviewers drawn from risk, legal, compliance and business teams, all internal functions that bill no client for the work. The efficiency claims on the site, ten times faster intake and sixty percent shorter cycle times, are aimed at the buyer's own throughput, which the value text records as not making the row a savings claim.
Nothing addresses billing, fee or disclosure treatment because there is no client invoice for it to address, and no fee terms of any kind were located in any event, since the customer agreement is negotiated individually and not published. Homepage, methodology page and terms of service checked 7 September 2026.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
The material exists and sits behind a request. Section 6.4 of the Terms of Use states that where a customer is subject to data protection laws requiring one, Credo AI will enter into its standard data processing agreement upon request, so the artifact a buyer would forward is not published. No subprocessor list was located on any surface, and no model provider behind the platform's own governance agents is named anywhere, so the question a client's AI clause actually asks, whose models see our content, has no published answer.
What is public and forwardable is narrower but real and should not be overlooked: the Terms of Use themselves carry the no-training commitment at 6.8, the named list of enterprise AI tools Credo AI staff may use with the confinement and deletion conditions attached, the sixty-day retention position, and the breach notification commitment. The trust center, which is where a subprocessor list would ordinarily sit, returns page metadata with no body on this channel and is the rebuttal route. Terms of Use read in full and trust center attempted 7 September 2026.
A current subprocessor list is published and the forwardable pack around it is thin. The privacy policy names four subprocessors, being Amazon Web Services, Microsoft Azure, Cloudflare and PostHog, and separately states that the AI tools are hosted through Microsoft Azure, which is more than a bare infrastructure list because it identifies where the AI processing happens. Hosting is stated to be in the United States, with Standard Contractual Clauses relied on for European transfers.
What is missing is the material a firm would actually forward and the answer a client's AI clause turns on. No data processing agreement was located on any surface. No customer agreement is published, since the terms of service state that services are provided under individually negotiated agreements, so the confidentiality, security and liability terms a questionnaire asks about cannot be sent in advance. And no model provider or model is named, only the host, so a customer cannot say whose model reads the vendor contracts and policy text that the platform parses.
The trust center states that it carries a subprocessor list and a hosting FAQ and returned no body on this channel; it is the rebuttal route. Privacy policy read in full, terms of service checked, trust center attempted, 7 September 2026.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
No located public material addresses court disclosure of AI use or a verification certification. The platform generates a great deal of evidence, including automated evidence generation, audit trails, audit-ready documentation and conformity artifacts, and it is worth being precise about whose that evidence is: it records what the customer's AI systems are and how they were governed, for regulators and auditors, not what Credo AI's own governance agents did to produce a given output.
Crediting it here would credit the customer's own mechanism to the vendor. Nothing read offers a per-item export covering which model or agent produced an assessment, what it retrieved and what a person verified, and nothing addresses a court's standing order on AI use or a disclosure a filer could attach. Product page and Terms of Use checked 7 September 2026.
Some elements of a record exist, built for a regulator rather than a court, and none of them records the model's own work. What the platform produces is substantial and well described: every governance action, including intake decisions, risk and impact assessments, approval records, periodic reviews and policy sign-offs, is logged with field-level precision and timestamped to the use case record, assembled as work happens rather than reconstructed, with exportable evidence packages available on demand and per-article gap analysis recalculated as the program changes.
An organization could show an auditor who decided what and when. What is absent is the limb this signal asks for. Nothing published offers a per-item record of which model or agent produced a given output, what it read, and what a person verified before the result was accepted, which matters because the platform's AI-assisted analysis can mark a control satisfied. Nothing addresses a court's standing order on AI use, and no certification or template a filer could attach is offered.
The distinction is that the record is of the customer's governance decisions, not of the model's part in reaching them. Compliance surface, homepage and methodology page checked 7 September 2026.
The questions both sides leave open
Derived from the records above rather than written, so it cannot favor either vendor. Take these into both conversations and ask each side the same question.
- Ethical Walls and Matter Segregation
- Good Law Verification
- Refusal and Uncertainty Behavior
- Bar Guidance Alignment
Which one fits
Choose Credo AI if
- You want the training bar and staff AI use in the contract. Credo AI's terms state that it will not use customer data to train any AI model, and name the enterprise AI tools its staff may use, confined to its own environment with the data deleted at the end of the engagement.
- Your AI estate runs across clouds, agent frameworks and GRC tools. Credo AI names integrations with AWS, Azure, GCP, Databricks and Snowflake, agent platforms such as LangChain and CrewAI, and ServiceNow, Archer and OneTrust, with SDKs and webhooks for the rest.
- You want agents to draft governance work under approval gates. Credo AI's GAIA agents handle intake, evidence retrieval, risk assessment and remediation, with approval gates in workflows and escalation to a person for high risk actions.
Choose Trustible if
- You answer to many AI frameworks at once. Trustible's experts read each framework in full and map every control to the articles it satisfies across more than fifteen frameworks, from the EU AI Act and Colorado's AI Act to NYDFS guidance and ISO 42001, so one control updates compliance everywhere.
- You want to know how much runs without a reviewer. Trustible publishes that 72 percent of use cases are approved automatically with an average review time of 1.8 days, and shows an activity feed of what its agents triaged, parsed and reassessed.
- Your security review wants a repeat attestation. Trustible states its third consecutive SOC 2 Type II, names the five areas the audit examined, and offers the report on request for due diligence.
In summary
Credo AI
Credo AI, based in Los Altos, California, sells an AI governance platform with an AI registry and shadow AI discovery, risk intelligence with automated red teaming, a compliance engine with policy packs for the EU AI Act, NIST AI RMF, ISO 42001 and SOC 2, and production monitoring of agent traces. Its GAIA agents handle intake, evidence retrieval, risk assessment and remediation. The AI Legal Index grades it in the top two bands on nine of fifteen capability axes, with an A on liability. Its published terms bar training on customer data, and it names Mastercard, Principal and AdeptID among customers. As of 7 September 2026 the index located no hosting region, named model or price.
Trustible
Trustible, an Arlington, Virginia public benefit corporation, sells an AI governance platform organized around intake, risk and impact management, monitoring and compliance, built on a control library that maps each control to more than fifteen frameworks including the EU AI Act, Colorado's AI Act, NYDFS guidance and ISO 42001. Agents parse vendor documents, analyze risk signals and check policy text against controls. The AI Legal Index grades it in the top two bands on seven of fifteen capability axes. It holds a third consecutive SOC 2 Type II, hosts its AI tools on Microsoft Azure, and names Leidos, Nuix and Guardian Life among customers. As of 7 September 2026 the index located no published customer agreement or price.
Questions buyers ask
Credo AI vs Trustible: which AI governance platform is better?
Credo AI sits in the top two bands on nine of fifteen AI Legal Index capability axes and Trustible on seven of fifteen, identical on nine. Credo AI publishes its terms, including a training bar and liability provisions, and names more integrations. Trustible publishes more about its method, its automation rate and its AI host. Buyers who need contract terms before a demo have more to read from Credo AI.
Do Credo AI and Trustible train AI on customer data?
Credo AI's terms state that it will not use customer data to train, develop or improve any AI model. Trustible's privacy policy states that it does not train its AI tools on personal information and that those tools do not retain it, a commitment framed around personal data rather than the governance content customers load. Trustible publishes no customer agreement. Graded by AI Legal Index against 15 capability axes and 12 legal signals, including privilege handling and citation accuracy, from each vendor's own published materials, verified September 26, 2026. No vendor pays for placement.
How does Trustible map controls across frameworks?
Trustible's policy and regulatory experts read each framework in full, normalize its obligations into controls, and map each control to every article it satisfies across more than fifteen frameworks. Designations such as High Risk, Provider and Deployer decide which controls apply to a system, and satisfying a control once updates compliance wherever it applies. Graded by AI Legal Index against 15 capability axes and 12 legal signals, including privilege handling and citation accuracy, from each vendor's own published materials, verified September 26, 2026. No vendor pays for placement.
Where do Credo AI and Trustible host data?
Trustible states that its services are hosted in the United States and that its AI tools run on Microsoft Azure, with Amazon Web Services, Cloudflare and PostHog also named as subprocessors. Credo AI publishes no hosting region or residency position on the surfaces this index could read; its trust center, the likely source, returned no content. Graded by AI Legal Index against 15 capability axes and 12 legal signals, including privilege handling and citation accuracy, from each vendor's own published materials, verified September 26, 2026. No vendor pays for placement.
What do Credo AI and Trustible both leave unpublished?
A price, a named model and a governance framework for their own AI. Neither publishes a rate, neither names the model behind its agents, and neither names who is accountable for its agents or reports testing before release, although both sell governance of other companies' AI. Neither describes what its agents do when they cannot ground an answer. Graded by AI Legal Index against 15 capability axes and 12 legal signals, including privilege handling and citation accuracy, from each vendor's own published materials, verified September 26, 2026. No vendor pays for placement.
Three readings to weigh. Credo AI's terms grant it a broad license to use, modify and publish customer content in connection with providing and improving its services, beside the clause barring model training; those are published terms. Trustible's training and retention commitments are stated as to personal information in its privacy policy, and its customer agreement is not published. Both trust centers returned no readable content on this index's check. Credo AI and Trustible were both verified on 7 September 2026. Neither vendor reviewed this page.
Neither vendor paid for inclusion, placement or a grade, and neither reviewed this page before it published. Everything above comes from public material on the dates shown. How the index grades.