Aracor AI
Aracor is a deal platform that reads the documents behind a transaction and keeps every finding tied to the language it came from. A team uploads a document set and Aracor returns a fully cited comparison of the terms without setup or prompting, runs structured due diligence workflows for reviewing and comparing corporate documents, produces one-click summaries of entire folders, and redlines contracts against preset or custom criteria either in the platform or in Microsoft Word. Optical character recognition handles scanned material and a signature verification feature checks that executed documents are valid. The claim the product is built around is traceability: every output is linked to the exact source language and the decision logic behind it, with sentence-level citations, so a conclusion can be defended rather than trusted. The deal environment updates as documents change, so legal, finance and corporate development teams work from one current record instead of reconciling separate copies, and non-English documents are supported. Security is architectural rather than bolted on. Aracor runs zero data retention by default, processing documents only during a session inside isolated execution environments, with encryption in transit and at rest, optional customer-managed encryption keys, role-based access control, multi-factor authentication and audit logging. It offers three deployment choices: cloud models managed by Aracor with access to OpenAI, Anthropic and Google systems; the customer's own API keys, so the customer keeps its own contract and terms with the model provider; or a private model deployed in the customer's own environment, including on premises or in a virtual private cloud. Its terms commit that neither the third-party models nor Aracor's own Legal AI Engine will be trained on customer content unless the customer explicitly consents. It is sold to investment funds, in-house legal and corporate development teams, and law firms handling mergers, capital raising and corporate advisory work. Aracor, Inc. is independent and led by its founder and chief executive, Katya Fisher.
Capability grades
All 15 axes, graded from public sources on the date shown. 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.
Remove the models and nothing remains to sell. Every function the product is described by is an inference over an uploaded document set: a fully cited term comparison produced without setup or prompting, structured due diligence workflows, one-click summarisation of entire folders, redlining against preset or custom criteria, sentence-level citation of answers back to source text, optical character recognition over scanned material, and signature verification. There is no document management system, no data room and no workflow product underneath that a buyer would license on its own; the deal environment exists to hold the documents the models read and the findings they produce. The agreement states the architecture rather than leaving it to marketing, article 4.5 recording that outputs are generated by third-party large language models enhanced by Aracor's own Legal AI Engine. Rebuilt from first-party retrieval 5 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.
Grounding is the product's organising claim and it is described concretely, while nothing about accuracy is measured. Outputs are stated to link to exact source language and decision logic, answers carry sentence-level citations drawn directly from the material, and term comparisons are delivered fully cited, so a reader can open the source and check the assertion against it, which is what the band asks for. The candour extends into the agreement: article 4.4 warns that outputs may not always be accurate and may contain material inaccuracies even where they appear accurate because of their level of detail or specificity, and that the customer should not rely on any output without independently confirming it, while article 9.4 records that the models are probabilistic. That is an unusually direct hallucination disclosure for a vendor selling defensibility. What is absent is any test of the claim: no accuracy figure, no evaluation, no test set, no error rate and no benchmark page appears anywhere on the estate, so the traceability architecture is documented and unquantified.
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.
The review obligation is written into the agreement and the threshold is not. Article 9.3 requires that the customer will not rely on any output without seeking the advice of, or vetting the output through, a duly licensed and qualified lawyer in the applicable subject matter and jurisdiction, and article 9.4 adds that output should be evaluated for accuracy as appropriate to the use case, including by ensuring qualified lawyer review. That is a written commitment placing a supervising lawyer between the model and the decision, and the review surface is real rather than nominal, since every output is tied to source language a reviewer can open. What is missing is the machine's side. Nothing states what runs unattended, and the marketing points the other way, selling a fully cited comparison in minutes with no setup and no prompting, which describes autonomous processing of an entire document set. No confidence signal, escalation path or error-handling route is described, and nothing addresses what happens when a cited finding is wrong.
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.
Attributed customers and published figures, joined loosely and dated nowhere. Two testimonials carry a full name, role and organisation: Nader A. Mettawa, General Counsel at Dabico Group, and Richard F. Christesen, Senior Commercial and Corporate Counsel at Constructor Group, whose account is linked to a case study whose own title claims 85 per cent of review time saved. A further customer story on the user stories page reports review time on large document sets cut by at least 40 per cent. A logo strip names eight organisations including Dabico Airport Solutions, Virtuozzo, Chainstack, Constructor Capital and Dutchess Management. Three things hold it below the top band and each is checkable. Nothing is dated and no method accompanies either percentage. Fuel Venture Capital appears in the customer logo strip and is also the lead investor in the company, which a reader should be able to see stated. And the first quotation in the user stories carousel is attributed to Kevin J. Sullivan, Senior Advisor, Aracor, which is the vendor's own advisor presented alongside customers.
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.
Among the strongest confidentiality architectures in this corpus, and the privilege limb is missing. Zero data retention is the default rather than an option: documents are processed only during a session, never stored or reused, inside isolated execution environments, with runtime isolation for every session, encryption in transit at TLS 1.2 or higher and at rest with AES-256, optional customer-managed encryption keys, role-based access control, multi-factor authentication and comprehensive audit logging. Downstream model providers are contractually required to support zero data retention, and article 4.6 commits that neither the third-party models nor Aracor's own engine will be trained on customer content without explicit consent. Article VI makes customer content the customer's proprietary information, and the deployment options let a customer keep processing inside its own environment entirely. Two things hold it here. No privilege or work product treatment appears anywhere, on a product built for transaction documents where privilege routinely attaches. And the same confidentiality clause qualifies itself, article 6.2 permitting use of proprietary information as necessary to facilitate the provision, improvement and enhancement of the services, with the obligation expiring five years after disclosure.
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.
A real published position, specific about jurisdiction, with no engagement with the professional rules themselves. Article 9.3 states that output may concern issues related to legal services or documents but is not formal legal advice, that Aracor's provision of services and all related output are for general informational purposes only, and that the customer will not rely on any output without seeking the advice of, or vetting the output through, a duly licensed and qualified lawyer in the applicable subject matter and jurisdiction. Naming the jurisdiction and the subject matter competence of the reviewing lawyer is more than a boilerplate disclaimer and is the substance of what the axis asks. Article 9.4 reinforces it, making the customer responsible for all decisions taken or not taken on the basis of output and requiring qualified lawyer review. What is absent is the professional layer: no bar association, rule of professional conduct or ethics opinion is named anywhere, and nothing addresses the supervision or competence duties of a firm putting a machine-produced diligence finding in front of a client.
AI Governance and Bias Disclosure
Published governance over model behaviour: who owns it inside the vendor, what is tested before release, and what is disclosed about disparate output across matter types, parties, or populations.
No governance position was located, and the estate carries a heading that promises one. The security page has a section titled Continuous Security and Responsible AI Development, and everything under it is security engineering: independent penetration testing, continuous vulnerability scanning, security reviews for new features, a controlled bug bounty with vetted researchers, threat modelling, secure coding practices, peer security reviews, red and blue team exercises and formal incident response procedures. Those are real and they are graded on the stewardship row. None of them is AI governance. Nothing published names a person or function accountable for model behaviour, describes pre-release evaluation of outputs, sets out an AI policy or principles, or addresses uneven performance, which on this product would bear on how findings behave across document types, deal sizes, languages and the non-English material the platform advertises support for. No ISO 42001 or equivalent is claimed. The site navigation and footer were inventoried on 5 September 2026 and the published policy set is the terms of service, the privacy policy and a data processing addendum.
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.
Retention, deletion and access are answered with unusual directness and the supplier picture is incomplete. Zero data retention is the default architecture: data is processed only during a session, never stored, logged or reused, in isolated execution environments, and downstream providers are contractually required to support the same. Article 8.3 gives the customer the option to delete customer content at any time in the product. Access controls are enumerated rather than asserted, covering TLS 1.2 or higher in transit, AES-256 at rest, optional customer-managed encryption keys, runtime isolation per session, role-based access control, multi-factor authentication and comprehensive audit logging. Testing is continuous rather than annual, with independent penetration testing, continuous vulnerability scanning, security review of every new feature and a controlled bug bounty, alongside formal incident response procedures. What keeps this off the top band is what a buyer still cannot see: no subprocessor register is published beyond the model providers and the two named payment processors, no hosting provider is identified for the Aracor-managed option, and no breach notification commitment or timeline was located in the terms or on the security page.
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.
The allocation of loss is published, readable before signing, and runs one way to an extent worth stating plainly. Article 10.1 caps Aracor's total liability for all damages, losses and causes of action, in contract or tort including negligence, at one dollar. That is the lowest cap located anywhere in this corpus and, on a product sold for merger and acquisition diligence where a missed obligation is the loss in question, it is effectively no recourse rather than a limited one. Article 9.1 provides the services as is with all warranties disclaimed, and article 9.2 disclaims specifically that the services will produce accurate or relevant content, that output will be satisfactory, and that Aracor has any control over the operation or continued availability of the AI models. Article 10.3 runs the indemnity from the customer to Aracor, covering use of the services, breach and interaction with customer content; there is no vendor-side indemnity of any kind, including for intellectual property. The only recourse published is commercial, a fourteen-day refund window under article 7.4. This is the middle band because the exposure the product creates is squarely addressed rather than unstated.
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.
One named surface a lawyer already works in, and nothing else. The product material states that contract review can be run in Word or in the Aracor platform, so Microsoft Word is a named integration with its function described at workflow level, and Aracor maintains a listing in Microsoft's own marketplace. That is the whole of it. No document management system is named, so nothing addresses iManage or NetDocuments; no virtual data room is named, which is a conspicuous absence on a diligence product whose input is a data room; no matter management, CLM or e-signature counterparty appears; and no API, developer documentation or field mapping was located on any page read. The agreement gestures at connections without specifying them, article 5.1 reserving rights in technology developed in connection with the services including integrations, while article 3.1(v) prohibits deploying software applications to run automated tasks against the service. A buyer would learn nothing about what moves between Aracor and their existing systems, or what they would need to configure.
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.
The tenancy limb is answered in more depth than anything else in this lane and the region limb is not addressed at all. Three deployment options are published and specified rather than listed. The first uses cloud models managed by Aracor, with data processed inside Aracor's isolated execution environment under zero data retention. The second routes requests through the customer's own API keys with the model provider, so the customer keeps its own contract, vendor terms and obligations, and Aracor acts solely as a secure interface. The third deploys a private model exclusively for the organisation, running either inside the customer's own environment including on premises or in its virtual private cloud, or in a fully isolated Aracor-managed deployment, with all computation and data remaining within the controlled environment. That is a genuine spectrum of isolation a buyer can match to a risk profile. Against it, no region is named anywhere for storage or processing, no cloud provider is identified for the Aracor-managed options, and no residency commitment appears in the terms or on the security page, which matters for a product sold into European transactions.
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.
Certification marks are displayed and the accompanying words stop short of claiming certification. Four badges appear on the home page and twice on the security page, an AICPA SOC mark, an ISO mark, a zero data retention mark and a GDPR mark. The sentence they sit beside says that processing happens within secure, isolated environments aligned with ISO 27001, SOC 2 and GDPR, and a later line says Aracor aligns with globally recognised standards. Aligned with is not certified, and the distinction is the whole question on this axis: no certification body is named, no certificate number, no examination period, no scope or statement of applicability, and no report or summary is published on any readable surface. A Security Whitepaper is offered in the resources list and its link resolves to an empty anchor. One retrieval limit is recorded and is not held against the vendor: a trust centre exists at a published subdomain, is linked from the home page and twice from the security page, and refused automated access through bot detection, so what it contains and whether it is self-serve or gated could not be established, and the lower tier is graded for that reason.
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.
Three of the four limbs are answered, two of them in the agreement itself rather than in marketing. Article 4.5 identifies the third-party large language models integrated into the service as OpenAI's GPT models, Google Gemini and Anthropic Claude, and names Aracor's own Legal AI Engine as the layer enhancing them, so a buyer learns from the contract which companies process its documents. The security page adds the supported zero-retention model set as ChatGPT, GPT-OSS, Claude and Gemini. The hosting arrangement is described in more detail than most records manage, through the three deployment options, and article 4.7 records that business licences have been purchased with those providers exempting uploaded data from model training. What fails is the fourth limb and one part of the first. No version is given for any model, so the naming is at product-family level only, and no commitment to notify customers when the model set or a provider changes was located anywhere, which matters because the customer's own risk assessment is built on which model is reading the deal.
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.
No pricing information is published at any level, including the unit of charge. There is no pricing page in the navigation or the footer, and every commercial route across the estate is the same one, talk to sales. Nothing states whether the service is charged per user, per deal, per document, per page or per organisation, no rate, band or minimum appears, no tier names are given, and no term length is stated, which is a live gap on a product whose three deployment options plainly carry different costs. The payment article describes mechanics rather than price: fees are payable in advance and non-refundable, a fourteen-day refund window applies to a new subscription, payment is processed by named third parties, and purchases may also be made through a distributor. One discrepancy is recorded because a buyer would notice it: article 7.1 obliges the customer to pay in accordance with the published prices, charges and billing terms in effect at the time, and no published prices were located anywhere on the estate. Searched the full navigation and footer on 5 September 2026. No pricing row is owed.
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.
Three buyer segments are defined with real specificity and the boundary is never drawn. Each has its own page and its own stated jobs: investment funds, broken out as private equity, venture capital, growth and family offices, buying to evaluate deals faster and spot issues early; in-house legal and corporate development, buying to keep deal terms aligned across stakeholders and maintain defensible records; and law firms, described as private equity, venture capital, mergers and acquisitions and corporate advisory practices, buying to accelerate reviews and keep work defensible. That is a clearer account of who the product is for than most records in this lane. Practice depth is transactional throughout, covering diligence, term comparison, negotiation, closing and post-closing obligations, and multi-language document support is claimed for global workflows. What is absent is the limit. Nothing states which transaction types or sizes the product does not suit, no jurisdiction is named for the diligence workflows, no firm or fund size is addressed, and the languages behind the multi-language claim are never listed.
Legal Signals
What each signal meansA signal records what public sources say on the date shown. It is not a grade and it is not a recommendation. Where a signal reads Not addressed, it means the index did not locate the material in public sources on that date, which is a statement about disclosure rather than about the product.
Client Data in Training
Can material a lawyer puts into this product be used to train a model?
Training occurs only where the customer has affirmatively enabled it.
The published agreement makes training conditional on the customer's affirmative consent, which is what this value records rather than an outright prohibition. Article 4.6 states that Aracor will not train any third-party large language model or its own Legal AI Engine on customer content unless the customer explicitly consents to that use. Article 4.7 supports it from the supply side, recording that business licences have been purchased with the integrated providers exempting uploaded data from being used for model training, and the security page adds that downstream providers are contractually required to support zero data retention and that data is never stored, logged or used for training. One qualifier belongs on the record and is not a training permission: article 4.8 allows Aracor to use customer content in anonymised form to support, monitor, improve or optimise the performance of the services, and to analyse non-identifying usage data for developmental and diagnostic purposes. That clause names neither training nor machine learning and is recorded rather than treated as consent.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
The customer sets the retention window and no retention is an available setting.
Zero retention is the published default rather than a setting a customer has to find. The security page states that Aracor enforces zero data retention by default, that data is processed only during a session and never stored or reused, that session data is handled ephemerally within isolated execution environments, and that downstream providers are contractually required to support the same, with no data stored, logged or used for training under the managed cloud option. The private deployment option keeps all computation and data inside the customer's own environment. Alongside that, article 8.3 of the terms gives the customer the option to delete customer content at any time within the service. One tension is recorded rather than smoothed, because a careful buyer will ask about it: an architecture that retains nothing and a product feature for deleting stored content at will do not sit together without explanation, and nothing published reconciles what persists in a deal environment described as staying current as documents change.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
The product maintains its own permission model, documented, requiring the firm to keep it aligned.
A separation architecture is described rather than asserted, at session level and at deployment level. The security page states that processing occurs in isolated execution environments and that there is runtime isolation for every session, so each piece of work is walled from the next rather than sharing a common workspace, and role-based access control and multi-factor authentication govern who reaches a deal inside a customer's own account. The third deployment option goes further, offering a model deployed exclusively for one organisation, running in the customer's own environment or in a fully isolated Aracor-managed deployment, with all computation and data remaining within that boundary. That is a documented mechanism, which is what separates this value from a bare claim. What is not addressed is the level a conflicted matter would require: nothing describes walls between deal teams inside a single customer, and the platform's design point is that legal, finance and deal teams all work from one shared view.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
Published terms or policy address disclosure to authorities or in response to legal process, and no commitment or reservation regarding customer notice is located anywhere. The vendor has told the customer that data can leave and has said nothing about whether the customer hears of it.
Compelled disclosure is addressed and customer notice is addressed nowhere. Article 6.3 of the terms lists the circumstances in which the confidentiality obligation ceases to apply, and the fifth is information required to be disclosed by law. That is an express carve-out reaching customer content, since article 6.1 defines the customer's proprietary information to include it, and the clause attaches no condition to the disclosure: there is no commitment to notify the customer before responding to a subpoena, court order or government demand, no reservation of discretion over notifying, no undertaking to limit the disclosure to what is legally required, and no route for the customer to seek a protective order. No transparency report exists. Two further limits are recorded: the confidentiality obligation itself expires five years after disclosure under the same article, and the data processing addendum published in the footer was not opened in this pass, so any notice provision it may contain is neither credited nor assumed.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
No located public material identifies the corpus behind the product’s answers.
No located material identifies a corpus, and the question does not bite on this product class. The material the models work on is the customer's own transaction documents, uploaded for a deal, and the product's defining claim is that every output traces back to that uploaded language rather than to any external body of law. There is no case law database, statutory source, publisher or licensed reference set behind an answer, and no market or precedent dataset is claimed. Recorded as the honest absence rather than a finding against the vendor. Searched the home page, the security page, the AI review product page, the terms of service and the site navigation on 5 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 authority is checked for subsequent history.
Nothing addresses checking authority for subsequent history, and the product neither retrieves nor cites primary law. Its citations run to the customer's own uploaded documents at sentence level, and its outputs are term comparisons, diligence findings, summaries and redlines. The nearest adjacent function is signature verification, which checks that an executed document is valid rather than whether a legal authority still stands, and it is recorded here so a reader sees it was weighed. The value is the honest absence rather than a finding against the vendor. Searched the home page, the AI review product page, the security page and the terms of service on 5 September 2026.
Refusal and Uncertainty Behaviour
What does the product do when the answer is not in the corpus?
No located public material addresses what the product does when it cannot ground an answer.
No located material describes what the system does when it cannot ground a finding. There is no abstention path, no no-answer state, no confidence indicator shown against an output, and nothing on behaviour where a document is illegible after optical character recognition, where a term appears in conflicting versions, or where a diligence question has no answer in the uploaded set. What the vendor does publish is a candid statement of the limitation rather than of the behaviour: article 4.4 of the terms warns that outputs may not always be accurate and may contain material inaccuracies even where they appear accurate because of their level of detail or specificity, and article 9.4 records that the models are probabilistic. Both place the burden on the reader to verify rather than describing the system recognising its own limits, and both are graded on the accuracy row. Searched the home page, the AI review page, the security page and the terms on 5 September 2026.
Fabricated Citation Record
Does a public court record exist involving output from this product?
No court order, opinion or disciplinary record naming this product has been located as of the date shown. This is a statement about the public record, not a finding about the product.
The AI Hallucination Cases database maintained by Damien Charlotin was searched on 5 September 2026 on the product name Aracor and on the corporate name Aracor, Inc. No court order, opinion or disciplinary record naming the product or the company was located. This records the state of the public record on that date and is not a finding about the product.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
Public materials refer to professional responsibility in general terms without naming guidance.
Professional responsibility is engaged in general terms and no authority is named. Article 9.3 of the terms requires that the customer not rely on any output without seeking the advice of, or vetting the output through, a duly licensed and qualified lawyer in the applicable subject matter and jurisdiction, and article 9.4 repeats the requirement for qualified lawyer review of probabilistic output. Framing the reviewer by licence, competence and jurisdiction rather than as a generic professional is a real engagement with the shape of the professional rules, which is why this sits above the floor. What is absent is any identified source: no bar association, rule of professional conduct, ethics opinion or regulator guidance is cited anywhere on the estate, no jurisdiction is named for the propositions asserted despite the agreement being governed by Delaware law, and nothing maps what a firm must do to discharge its own supervision and competence duties when a diligence finding produced by the platform reaches a client.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
Public materials claim time savings without addressing billing or disclosure.
Time savings are published with figures and nothing addresses the billing consequence. The estate carries a customer account of review time on large document sets cut by at least 40 per cent, a case study whose title claims 85 per cent of review time saved, and a testimonial that what used to take hours of review now takes moments. All of it is directed at speed and at the buyer's own capacity. None of it reaches the question this signal asks, which is what happens to the bill when diligence that took a week takes a day. No per-matter record of AI-assisted work is described as available, no guidance on fee or disclosure treatment is published, and nothing addresses what a law firm client is told when the diligence report supporting a transaction was machine-produced. The direction is worth recording on this record because two of the three named buyer segments are law firms and in-house teams who bill or account for that work onward, and the platform captures the underlying activity in its audit trail without offering it for that purpose.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
A current subprocessor or model provider list is published.
The model providers are named in the agreement itself, which is the hard part of this question, and the full pack was not established. Article 4.5 identifies the integrated third-party large language models as OpenAI's GPT models, Google Gemini and Anthropic Claude, and article 4.6 commits that none of them nor Aracor's own engine trains on customer content without explicit consent, with article 4.7 recording business licences that exempt uploaded data from training. Because the terms are public, a firm can forward that language to a client verbatim without a sales conversation, and can add the security page's account of zero data retention and isolated execution. What was not established is a subprocessor register: no hosting provider is named for the Aracor-managed deployment, and beyond the model providers and the two named payment processors no list exists. A data processing addendum is published in the footer and was not opened in this pass, so its contents and any subprocessor annex are neither credited nor assumed; it is the cheapest available upgrade on this row.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
Some elements of the record are available, short of a document level export.
Real elements of the record exist as a property of the product, short of anything built for disclosure. Every output is stated to be tied to the source language and the decision logic behind it, answers carry sentence-level citations into the underlying document, and the security page claims full auditability alongside comprehensive audit logging. That is more than a platform activity trail: a firm can show which passage a finding rests on and, on the vendor's account, the logic that produced it, which is the sources-retrieved element this signal contemplates. What is missing is the rest. No model or version is identified against any individual output, nothing records that a human reviewed a finding despite the terms requiring qualified lawyer review, and no export is designed or described for producing any of it to a client, a counterparty or a tribunal. No disclosure template or guidance is published. The zero-retention architecture cuts against reconstruction after the fact, since a session that stores nothing leaves less to produce later.