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Conga CLM

Conga CLM is the contract lifecycle management product in Conga's commercial operations suite. It covers contract requests and generation from approved templates and clause libraries, approval workflows, negotiation, electronic signature, a searchable repository, obligation and renewal tracking, and reporting. It comes in two forms, the original application built on Salesforce and a software as a service edition on the Conga Advantage Platform that works alongside any CRM, ERP or procurement system.

Authoring happens in Microsoft Word, Google Docs or a browser editor. The AI, AiMe, runs across the whole suite. In contracting it imports third party, legacy and acquired agreements in bulk and turns them into structured data. It compares drafts against a negotiation playbook, flags risky clauses, proposes redlines, summarizes agreements and answers questions about the repository. Generative features run on Microsoft Azure OpenAI.

Tenant permissions and dedicated encryption keys control access, and customers validate AI recommendations before acting. Named customers include Southwest Airlines, LinkedIn, AXA, Peloton and Cotality. Conga Corporation is based in Broomfield, Colorado.

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Conga CLM, head to head

Side by side on the same 15 capability axes and 12 legal signals: where the two part company, and what neither one publishes.

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Ordered by how closely the graded profiles match across the 15 capability axes, inside the same categories. See how each axis is graded in the methodology.

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.

BB on AI CentralityThe models are the engine of a core capability, layered on a product that would still function without them as a document or workflow system.

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.

AiMe is a shared AI layer across the commercial suite. It connects workflow data across CPQ, CLM, price optimization and document automation and suggests next steps, rather than being the CLM itself. Underneath sits a full contract lifecycle platform that long predates it, with template and clause library generation, approval routing, negotiation, electronic signature through Conga Sign, a searchable repository, obligation and renewal tracking, and reporting.

The models drive core features on top of that platform. Without AiMe a working CLM remains, as the edition built on Salesforce was for years. Recent releases push AI further in. The June 2026 release extends AI across the platform, including bulk import and extraction for incoming contracts. The March 2026 AiMe release adds agents that act inside quoting and contracting workflows. Conga still sells and prices the platform as a contract system with intelligence on top.

Source: Vendor Published
BB on Citation Accuracy and Hallucination DisclosureGrounding is real and documented, with linked primary sources and a described retrieval method, short of published accuracy figures an outsider can test.

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.

The AI pipeline divides document processing among specialized providers. Google Cloud Vision handles optical character recognition, Amazon Textract table detection, Zuva provision extraction and Azure OpenAI language processing. Output is grounded in the customer's own repository, playbook and clause library, and extraction needs no model training by the customer. AiMe shows how every recommendation is generated, with the reasoning visible and confidence scores wherever it makes a suggestion.

The Artificial Intelligence Addendum addresses accuracy only through a disclaimer. It states that outputs may be inaccurate, incomplete or misleading and disclaims any warranty of accuracy or completeness. No accuracy figure, test set, error rate or benchmark result is available. Third party models undergo benchmarking before release, without disclosed results. The product cites no legal authority, so grounding in authority and citator checks do not apply.

Source: Vendor Published
AA on Autonomy and Oversight ModelWhat the system runs alone, what constrains it, and how a lawyer checks it are all published: modes, thresholds, review surfaces, and the route a matter takes back to human judgment. A categorical limit on a named mode or tier, stating what its output may not be used for, meets the threshold limb without a number.

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.

AiMe never acts autonomously on high stakes decisions, Conga states. Three mechanisms constrain it, agent guardrails, approval thresholds and human in the loop confirmation, and each can be built into a workflow. AiMe shows how every recommendation is generated and the reasoning behind AI driven actions. Confidence scores appear wherever it makes a suggestion, users accept or reject redlines, and every action and approval is kept in an audit trail.

Much of the oversight model is written into the contract. The Artificial Intelligence Addendum makes the customer solely responsible for evaluating and validating outputs. It says the customer must not rely on AI outputs as the sole basis for any decision with legal, financial, regulatory or other material impact. It also requires human review and independent judgment, and puts authorizing and supervising agent actions on the customer.

The guardrails and thresholds are described as configurable rather than as defaults, and the same document states that Conga does not monitor or review AI generated outputs.

Source: Vendor Published
BB on Operational and Outcome EvidenceReal deployment evidence with substance, short of full attribution or measurement: a named customer without figures, or figures without the named customer.

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.

Cotality, formerly CoreLogic, describes improving client service with Conga CLM in a September 2024 customer story without a quantified outcome. Two other dated stories, DigiKey on price management and Kalixia at 160 times faster document generation, concern other Conga products. Other named customers include Southwest Airlines, LinkedIn, AXA, Peloton, Cotality, T-Mobile, Adobe, Box and Kraft Heinz. The headline improvement figures are separate from those named customers.

A 9 percent revenue increase appears beside the logo strip with no stated basis, and Conga claims 50 percent less review time with AI. Conga also cites G2 Leader recognition across five grids.

Source: Vendor Published
BB on Privilege and Confidentiality PostureSubstantive published commitments on confidentiality and training use, short of the full picture: commonly silence on segregation between users or matters, or on what the underlying model provider may retain.

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.

Under the Artificial Intelligence Addendum, Conga will not use AI Inputs or AI Outputs to train or improve any model beyond a limited license to provide, maintain or improve the Services for that customer. Customer Data will not train global or foundational models serving multiple customers, and no third party may use Customer Data or AI Output to train, fine tune, validate, test or develop any model. Tenants are logically separated with dedicated encryption keys.

The Data Processing Addendum limits retention to the time absolutely necessary and requires return and deletion at the customer's election after the agreement ends. Prompts, completions, embeddings and training data sent to Azure OpenAI are not available to OpenAI and are not used to improve OpenAI, Microsoft or third party products. Each document processing provider works under a zero retention arrangement. Conga sells the product to legal departments to hold their agreements, and its addenda, trust center and product pages do not address attorney client privilege or work product. Separate contractual conditions sit in Conga's Master Services Agreement.

Source: Vendor Published
BB on UPL and Professional Responsibility PostureA real position is published on advice versus tooling, short of full treatment: commonly a disclaimer without the supervision and competence dimension, or silence on jurisdiction limits.

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.

Conga's position on advice versus tooling sits in the Artificial Intelligence Addendum. The Addendum states that AI generated outputs may be inaccurate, incomplete or misleading, disclaims any warranty of fitness, and makes the customer solely responsible for validating outputs before use. It says the customer must not rely on AI outputs as the sole basis for any decision with legal, financial, regulatory or other material impact, and that human review and independent judgment should be exercised.

It applies the same rule to agents, making the customer responsible for deciding whether agent actions are appropriate and for authorizing and supervising them. Legal, sales and procurement teams use the application as a contracting tool. The service does not specify how a supervising lawyer meets competence or oversight duties over AI drafted contract language. Neither capability restrictions by buyer group nor jurisdictional limits appear in the terms. The product is marketed to sales and procurement users who generate contract positions in the same tenant as legal.

Source: Vendor Published
BB on AI Governance and Bias DisclosureA published governance framework with real substance, short of testing results or a named owner.

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.

Conga's AI governance framework sits in the Artificial Intelligence Addendum rather than on a principles page. The Addendum records a cross functional AI Governance Committee responsible for oversight of AI within the Services. The committee focuses on risk management, accountability and compliance, and periodically reviews AI risks, controls and mitigations. Conga commits to internal policies on responsible AI covering oversight of training data, bias mitigation and human interpretability, to staff training, and to full cooperation with a customer's own AI impact assessments.

Governance is tied to the NIST AI Risk Management Framework and its four functions, Govern, Map, Measure and Manage. The vendor classifies its products as minimal or limited risk AI systems under the EU AI Act. It states that third party models are tested, audited for bias and benchmarked before release, with rollback to any prior model version within hours. Results from that testing, bias audit findings, evaluation outputs and model cards are not available, including performance differences across contract types.

Source: Vendor Published
AA on AI Safety and Data StewardshipRetention, deletion, access control, subprocessors and incident practice are all published, current, and specific enough to hold the vendor to.

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.

The Data Processing Addendum says retention of personal data should generally not be required and is limited to the time absolutely necessary to perform the Services. Daily backups are kept for thirty days, and each third party document processing provider works under a stated zero retention arrangement. Data is returned or deleted at the customer's election within a reasonable period after the agreement ends, and the CCPA attachment requires prompt compliance with deletion requests.

Access controls include role based authorization, least privilege, quarterly access reviews, multifactor authentication, encryption at rest, TLS of 256 bits or stronger in transit, and per tenant encryption keys. The subprocessor terms provide fifteen days' notice before additions, a right to object with termination and refund, and Conga's responsibility for provider acts. Incident notice comes within 48 hours of Conga becoming aware, backed by a response plan with root cause analysis and a 24/7 security team.

Source: Vendor Published
CC on AI Liability and RecourseLiability is addressed only through a standard limitation clause that disclaims the exposure the product creates.

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 Artificial Intelligence Addendum states that Conga makes no warranty, express or implied, on the accuracy, completeness, noninfringement or fitness for purpose of AI generated output. The customer is solely responsible for evaluating and validating that output. To the maximum extent permitted by law, Conga is not liable for any losses, damages or claims arising from the customer's use of or reliance on AI output or on actions by agentic AI features.

That includes third party claims. One allocation runs the other way. The Data Processing Addendum makes Conga liable for its subprocessors' acts and omissions as if it had performed the services itself, and much of the AI pipeline sits with those third parties. The addenda do not state a general liability cap, an indemnity scope or an insurance position. Conga's Master Services Agreement is a separate document.

Source: Vendor Published
BB on Practice Systems Integration DepthReal integrations exist and are documented, short of depth: named connections without a description of what they actually move.

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.

Several of Conga CLM's integrations are structural. One edition runs natively on Salesforce and is listed on the Salesforce AppExchange. Authoring and review run inside Microsoft Word and Google Docs, and Microsoft Dynamics is named on the product page. The platform edition supports connections to CRM, ERP and procurement systems. Within Conga's own products, pricing, terms and configurations flow from CPQ into a contract.

Documents are generated through Composer and signed through Conga Sign, and price optimization feeds contract pricing. Developer resources cover APIs and integrations. Conga does not document field mapping or sync direction for individual external connectors.

Source: Vendor Published
BB on Deployment Model and Data ResidencyDeployment model is stated clearly with partial residency detail, or residency is offered without the processing location being addressed, or the tenancy model is stated on its own with no residency detail published.

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 CLM has two delivery forms. One is the original application built on Salesforce. The other is a software as a service edition on the Conga Advantage Platform that gives buyers a CLM interface independent of Salesforce. The Data Processing Addendum treats them differently. It states that Conga does not back up customer data for services hosted on Salesforce and sets no recovery point objective for them. Elsewhere it keeps daily backups for thirty days, with a one hour recovery point objective and a twenty four hour recovery time objective.

Infrastructure is named as Salesforce, Amazon Web Services and Azure, with data on servers managed by Salesforce and AWS. Each logical tenant boundary has its own encryption key. Availability is described as spanning the United States, the European Union and Asia Pacific with residency options included, which names continents rather than regions. Conga gives no region list, no method for choosing a tenant's region and no separate processing locations.

Content reaches Azure OpenAI, Google Cloud Vision, Amazon Textract and Zuva, and Conga does not say where those services process it.

Source: Vendor Published
BB on Security Certifications and Trust CenterCertification is real and stated, short of accessible evidence: a named standard without scope, date, or a way to obtain the report.

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.

SOC 2 Type II covers the full platform under annual audits, according to Conga. The trust center also lists ISO 27001, ISO 27701 as its privacy extension, PCI DSS, HIPAA Security with annual audits, GDPR and CCPA. It adds alignment to the NIST AI Risk Management Framework and certification under the EU-U.S. Data Privacy Framework. The Data Processing Addendum links that certification to the Department of Commerce register.

The security program includes annual third party penetration testing, application vulnerability assessment twice a year, continuous automated threat hunting and code analysis before release. It also covers a patching service level by severity, background checks, annual security training and a vulnerability disclosure program. Auditor names, report periods, observation windows and certificate numbers are not available alongside those claims, and reports require a request.

The Data Processing Addendum makes reports available on a customer's request under confidentiality, so a prospective buyer cannot read the audit scope before signing.

Source: Vendor Published
BB on Model Supply Chain DisclosureThe supply chain is partly disclosed: providers named without change notification, or architecture described without the providers.

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.

Generative features run on Microsoft Azure OpenAI. The document processing agents also use Google Cloud Vision for optical character recognition, Amazon Textract for table detection and Zuva for provision extraction, each under a stated zero retention arrangement. The Azure OpenAI Service is described as fully controlled by Microsoft, hosted in Microsoft's own Azure environment and not interacting with any system operated by OpenAI.

Prompts, completions, embeddings and training data are tokenized in transit, are not available to OpenAI, and are not used to improve OpenAI, Microsoft or third party models. Change notice is contractual. The AI providers are subprocessors, and the Data Processing Addendum gives fifteen days' notice before a new one is appointed, with its name, location and activity. It also gives a right to object, and termination with a refund if no workaround exists.

No specific model is named. The Addendum refers to Azure OpenAI GPT, which is a family rather than a version, and nothing states which model writes a summary or a redline or when that changes.

Source: Vendor Published
DD on Commercial TransparencyNo pricing information published at any level, including the unit of charge.

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.

Conga CLM uses custom quotes without a numeric starting rate, a defined billing unit or a plan table. The application combines drafting, negotiation, approvals, electronic signature, contract storage and obligation management, with AI review and extraction inside that workflow. Additional products connect CPQ, document generation and signing to the wider suite. An advanced CLM feature set includes clause libraries, version control and redlining, with no incremental charge given for it.

Subscription duration, renewal provisions, price increase limits and implementation fees are not given with the quote request. The Master Services Agreement is separate from the AI and data processing addenda.

Source: Vendor Published
BB on Firm and Practice CoverageSegment and practice coverage is described with substance, short of the boundaries: what is supported is clear, what is not is left open.

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.

Legal, procurement, sales, finance, IT, business operations and pricing teams use the suite. Their CLM tasks differ. Legal gets workflow, authoring, AI review and redlining, compliance and risk management. Procurement gets obligation management, AI extracted terms and pricing. Sales gets generation, AI assisted negotiation and renewals. Industry uses cover technology, financial services, healthcare, life sciences, manufacturing, transport and logistics, and distribution.

Named customers span airlines, insurance, media, retail and property data. No practice area inside a legal department is named as supported or unsupported, and nothing states what the product is not for. Conga sets out no capability restrictions for users who are not lawyers inside a shared tenant. Nor does it draw jurisdiction or language coverage boundaries, although the product is localized into German and French.

Source: Vendor Published
Sources on file

5 public documents

The public pages on file for Conga CLM, with the recorded signals each one supports and the date it was last read. Open any of them and check the reading against the record.

Change log

Product updates

Oct 12, 2026Integration / interoperabilityVerified

The Oct '26 release of Conga CLM for Salesforce adds the CLM AI Library, a package that opens agreement lifecycle actions to Agentforce and Claude through Conga's Model Context Protocol capability. From a natural language prompt, users can create agreements, generate documents, import offline paper, send agreements for review or signature, and activate them. Administrators install the package and choose which capabilities to configure.

Bears on: Autonomy and Oversight ModelSource
Sep 22, 2026Product / capabilityPartially Verified

Conga CLM for Advantage Platform release 202609.1.0, published to Preview on 22 September 2026, adds Supplier Sanctions Screening, which checks one or many suppliers against the OFAC SDN List and the UN Consolidated Sanctions List and emails per supplier PDF reports. Screening runs on a purpose built AI skill using exact match logic with no score or fuzzy matching, and it never blocks a supplier automatically: an authorized user must block with a recorded reason, after which linked contracts show a Blocked tag and their workflow actions pause.

Bears on: Autonomy and Oversight ModelSource
All Conga CLM updates →

Legal Signals

What each signal means

A 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.

Confidentiality and Privilege

Client Data in Training

Can material a lawyer puts into this product be used to train a model?

Permitted, in the contract

The published agreement expressly reserves a right to train on customer content, with no opt out located. Any de identification, anonymization or aggregation qualifier is recorded in the summary.

The Artificial Intelligence Addendum expressly permits training on customer content, within written limits. Section (c) says Conga will not use Customer Data to train global or foundational models that serve multiple customers. Any training on Customer Data is limited to models specific to the customer's instance or tenant. Permitted training is limited to the customer's own data and a model only that customer uses, and neither the Addendum nor the trust center describes an opt out.

Conga does not use Customer Data to train third party foundational models, naming Azure OpenAI GPT as the example. Section (d) says Conga will not let any third party use Customer Data or AI Output to train, fine tune, validate, test or otherwise develop any AI model. Section (b) says that, beyond a limited license to provide, maintain or improve the Services for that customer, Conga will not use AI Inputs or AI Outputs to train or improve any model.

The trust center adds that models trained on one customer's data are never used for another. One carve out is reserved. Service Attributes, defined as anonymized and aggregated usage information, may be used to train and refine models and are stated not to be Customer Data.

Source: Vendor PublishedAny model training using Customer Data shall be limited to models specific to Customer's instance or tenant.As of Sep 12, 2026Evidence

Prompt and Output Retention

How long does the product keep what a lawyer typed, and can that be set to zero?

Customer controlled, no zero option

The customer controls the retention window, by product configuration or by contractual instruction, but zero retention is not stated as available.

The Data Processing Addendum lets the customer control retention by contractual instruction. Attachment A sets the default. Retention of personal data should generally not be required, and any retention is limited to the time absolutely necessary to perform the Services. Section 9.6 requires return and deletion at the customer's election within a reasonable period after the agreement ends, with the customer deleting within the Services and Conga helping where it cannot.

The CCPA attachment adds a duty to follow any customer deletion instruction promptly. Daily backups are kept for thirty days, except for services hosted on Salesforce, which Conga does not back up. At the model layer, Conga states a zero retention policy with each third party document processing provider. Documents sent to Azure OpenAI, Google Cloud Vision, Amazon Textract and Zuva are therefore processed in real time and not stored. No zero retention setting is offered to the customer inside the Services.

Source: Vendor Publishedany retention period will be limited to the duration absolutely necessary to perform the ServicesAs of Sep 12, 2026Evidence

Ethical Walls and Matter Segregation

Does retrieval respect the firm’s ethical walls, or can the model read across them?

Own model, documented

The product maintains its own permission model, documented, requiring the firm to keep it aligned.

Conga CLM has its own permission model, which the customer administers. Between customers, separation is built into the architecture. Tenant environments are logically separated, each with its own encryption keys, and models trained on one customer's data are never used for another customer's recommendations or scores. Inside a tenant, the Data Processing Addendum's security attachment requires role based authorization, least privilege, quarterly access reviews, multifactor authentication and the customer's ability to limit access to authorized personnel.

Rules based access controls, audit logs and admin tools help the customer configure and manage AiMe, which leaves the alignment work with the customer. The product does not apply an outside document management system's access model at query time. The addenda and trust center do not address segregation between matters or business units inside one tenant. The platform is sold to legal, procurement, sales, finance and IT in the same instance, and the assistant answers questions across the whole contract repository.

Source: Vendor PublishedAiMe tenant environments are logically separated with dedicated encryption keysAs of Sep 12, 2026Evidence

Third Party Request and Subpoena Notice

If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?

Notice committed

Terms commit to notice where lawfully permitted. No transparency report located.

Section 4 of the Data Processing Addendum's security attachment is headed Disclosure by Law. If Conga is required by law to disclose customer data, it will notify the customer as soon as practical where the law permits. It will also take all steps to give the customer an opportunity to prevent or limit the disclosure, an obligation to help and not only to inform. The CCPA attachment adds a slightly stronger commitment for personal information.

For a legally required disclosure unrelated to the contracted business purpose, Conga must first tell the customer and give it a chance to object or challenge the requirement, unless the law prohibits notice. Conga will also redirect a misdirected data subject request to the customer and will not respond without the customer's prior written consent unless legally required. No transparency report, aggregate demand count or reporting cadence is available.

Source: Vendor Publishedgive Customer prior notice of the obligation as soon as practical after becoming aware; and take all steps to enable Customer an opportunity to prevent or limit the disclosureAs of Sep 12, 2026Evidence
Accuracy and Authority

Primary Law Corpus Provenance

Where does the law in this product come from, and does the vendor have the right to use it?

Sources named, basis unstated

Sources are identified without stating the license or rights basis.

Conga CLM works from the customer's own material. That means contracts imported in bulk, including third party, legacy and acquired agreements, plus the customer's clause library, negotiation playbook and approved templates. The vendor states that precise models are built from the customer's own documents without the customer having to train them. The generative layer is named too. Azure OpenAI handles language processing, with Google Cloud Vision, Amazon Textract and Zuva for optical character recognition, table detection and provision extraction.

Conga states no rights basis for any of these sources and does not describe what the underlying foundation models were trained on. Zuva's extraction models are trained on contract collections rather than on the customer's documents, and they are named without any account of what sits behind them. On the customer's side, the Artificial Intelligence Addendum leaves the customer with all right, title and interest in its AI Inputs and AI Outputs and grants Conga only a limited license.

Source: Vendor PublishedAs of Sep 12, 2026Evidence

Good Law Verification

Does the product tell you when the authority it just cited has been overruled?

Not addressed

No located public material addresses whether authority is checked for subsequent history.

The product cites no cases, statutes or regulations, so checking authority for later history does not arise in its usual form. It works on the customer's own agreements, comparing drafts to a negotiation playbook, matching against an approved clause library, extracting obligations and dates, summarizing, and answering questions about the repository. Nothing it produces is a statement about the law that a lawyer would check for later treatment.

The nearest point is obligation and renewal tracking, where the question is whether a contractual date or duty is still live, and alerts and dashboards handle that. No feature checks legal authority for subsequent history.

Source: Vendor PublishedAs of Sep 12, 2026Evidence

Refusal and Uncertainty Behavior

What does the product do when the answer is not in the corpus?

Confidence signal only

The product exposes a confidence or grounding score without an explicit abstention path.

Conga commits that AiMe shows how every recommendation is generated, that users see the reasoning behind AI driven actions, and that confidence scores appear wherever AiMe makes a suggestion. That gives a reviewer a signal for each suggestion. Conga does not describe what the system does when it cannot ground an answer. It names no explicit refusal response or unsupported extraction marker. Nor does it say what happens when a clause cannot be matched to the playbook or a question cannot be answered from the repository.

No evaluation results for that behavior are available. The Artificial Intelligence Addendum allocates the consequences instead. It says outputs may be inaccurate, incomplete or misleading, makes the customer solely responsible for validating them, and states that Conga does not monitor or review AI generated outputs. How the guardrails behave in practice is left unexplained.

Source: Vendor Publishedconfidence scores are shown wherever AiMe makes a suggestionAs of Sep 12, 2026Evidence

Fabricated Citation Record

Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?

None located

No court order, opinion or disciplinary record addressing fabricated or hallucinated legal citations produced by this product has been located as of the date shown. This is a statement about the public record on that one subject, not a finding about the product, and this signal is not a litigation history.

The AI Hallucination Cases database maintained by Damien Charlotin tracks decisions worldwide where a court addressed hallucinated AI content, and records the tool implicated where known. It records no court order, opinion or disciplinary record naming Conga CLM or Conga. Two independent sanctions trackers of decisions on AI generated fabricated citations do not name them either. Conga CLM works on contracts and cites no legal authority, so its output does not ordinarily reach a court filing.

Source: Bar Guidance or Court RecordAs of Sep 12, 2026
Professional Responsibility

Bar Guidance Alignment

Has the vendor engaged in public with the ethics opinions its buyers are bound by?

Not addressed

No located public material engages with bar or ethics guidance.

No bar or ethics guidance is named for the service. ABA Formal Opinion 512 does not appear, no state guidance on generative AI in legal practice is referenced, and nothing maps a capability to a jurisdiction's rules of professional conduct. Conga does cite outside frameworks, but none of them is professional responsibility guidance. The Artificial Intelligence Addendum ties governance to the NIST AI Risk Management Framework, and the trust center classifies the products as minimal or limited risk AI systems under the EU AI Act.

Both are addressed to the vendor as an AI provider. The nearest thing to a professional responsibility statement is the Addendum's requirement that the customer not rely on AI outputs as the sole basis for a decision with legal impact. It also requires the customer to exercise independent judgment. It names no guidance.

Source: Vendor PublishedAs of Sep 12, 2026Evidence

Billing and Fee Posture

Does the vendor address what happens to the bill when the work takes an hour instead of six?

Outside the fee relationship

The product does not touch a fee between a lawyer and a client. It operates before an engagement exists, or it is bought by a team that bills no client for the work. Savings claims aimed at the buyer’s own cost are recorded in the summary and do not make the row a savings claim, because no client bill is in the loop.

The product serves corporate teams managing their own commercial agreements. The named audiences are in house functions, legal, procurement, sales, finance, IT and business operations, each with its own page. The named customers are corporate, among them an airline, an insurer, a property data business, a consumer fitness company and a professional network. Nothing is addressed to a law firm billing a client. Conga's efficiency claims include a 9 percent revenue increase, 50 percent less review time with AI, faster deal cycles and lower supplier costs.

All of them concern the buyer's own cost, cycle time or revenue, and none reaches a client bill. The platform also runs quoting, pricing and billing, but that is the customer billing its own customers rather than a lawyer billing a client. No client fee disclosure workflow for AI assistance is specified.

Source: Vendor PublishedAs of Sep 12, 2026Evidence

Outside Counsel Guideline Readiness

Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?

Disclosure pack published

A subprocessor and model provider list plus client facing disclosure material is published or available without an agreement in place.

Customer counsel can use the AI and data processing addenda to address a counterparty's AI clause. Conga's trust center names Google Cloud Vision for optical character recognition, Amazon Textract for table detection, Zuva for provision extraction and Azure OpenAI for language processing. It states a zero retention arrangement with each and explains what Azure OpenAI does and does not do with prompts and completions.

The subprocessor register identifies the supporting services. The Data Processing Addendum applies Clause 9(a) Option 2 of the Standard Contractual Clauses to that list, with fifteen days' notice, a right to object and termination with a refund. The Data Processing Addendum includes the standard contractual clauses and their UK and Swiss adaptations, alongside the separate Artificial Intelligence Addendum.

Source: Vendor PublishedConga's Discovery Agent and Q&A Agent use a small number of specialized third-party services for document processing, including Google Cloud Vision (OCR), AWS Textract (table detection), Zuva (provision extraction), and Azure OpenAI (language model processing).As of Sep 12, 2026Evidence

Court Disclosure Support

If a judge’s standing order requires an AI disclosure, can the product produce one?

Partial record

Some elements of the record are available, short of a document level export.

The platform keeps a complete audit trail of every action, approval and signature across the contract lifecycle, which the vendor describes as supporting legal or internal reviews. It also keeps version control, tracked edits and inline comments. AiMe shows how every recommendation is generated and the reasoning behind AI driven actions, and confidence scores accompany each suggestion, so the basis of a proposed clause is visible at review.

No described report or extract identifies which model produced a passage, and Conga names the model only by family. Conga describes no document level export, no marking of machine generated text against human edited text in a form a party could give a court, and no disclosure template, certification form or court guidance.

Source: Vendor PublishedMaintain a complete audit trail of every action, approval, and signature in the contract lifecycleAs of Sep 12, 2026Evidence
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AI Legal Index

The AI Legal Index is an independent index that tracks changes to AI vendors in legal. It holds 462 vendors across 9 categories, each graded on the same 15 capability axes and recorded against 12 legal signals, from public sources. No vendor pays for inclusion, placement, or rating.

Index Status
Last index update
October 21, 2026
The AI Legal Index is an editorial reference. It is not a regulatory body, not a law firm, and nothing published here is legal advice or a recommendation to retain or avoid a vendor. Records are verified against published sources, bar guidance and public court records. Where a record reads not addressed, the material was not located in public sources on the date shown. See the Methodology page for evaluation standards and limitations.
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