Conga CLM vs Leah: how they compare in 2026

AiMe is described as a shared AI layer running across the whole 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 is described as enhanced by AI throughout, and bulk import and extraction is presented as the way contracts enter the system. 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.

Leah sells AI agents and an orchestration layer that sit on top of a contract lifecycle platform, and that platform works without them. The vendor describes it the other way round. It says other vendors bolted AI onto systems built for manual workflows, while Leah was designed from scratch with orchestration as the foundation. ContractPod Technologies has sold contract lifecycle management since 2012. Leah launched in March 2023 as an AI services hub within that platform, went standalone in May 2023, and Leah Intelligence followed in October 2024. Without the agents, the product is still a working CLM with guided intake, approval routing, DocuSign and Adobe Sign execution and a contract repository. That CLM has its own market and its own Gartner category placement. The orchestration layer on top is model driven.

Conga's trust center names each part of the AI pipeline. 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. Conga publishes no accuracy figure, test set, error rate or benchmark result. It says third party models are benchmarked before release, and publishes no results. The product cites no legal authority, so grounding in authority and citator checks do not apply.

Leah returns to accuracy repeatedly in its materials, and the AI governance page says every action is measured against benchmarks for accuracy, bias and outcome. Neither that page nor the home page publishes a result from that measurement. They give no accuracy figure, no error or hallucination rate, no description of any benchmark or test set and no published evaluation. The product material describes a legal helpdesk that answers contract questions with sources attached, so a user can in principle check an answer against its source. Neither page says what the system does when the customer's own contracts do not support a position.

Conga states that AiMe never acts autonomously on high stakes decisions. 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.

Leah's dedicated AI governance page sets out a three stage control loop. In the first stage, policy in, the customer defines which agents may act, on which data, within which thresholds and where escalation is required. Those policies are held as configuration rather than code. In the second, execution governed, every agent action runs through those policies in real time. Approvals, escalations and rejections are applied automatically, and the orchestrator enforces guardrails at each step. In the third, audit out, every decision is logged with the rationale, what the agent did, why, under which policy, on what data and to what outcome. The records are described as tamper resistant and immutable. The loop sets the thresholds, the review points and the route back to human judgment. Leah's home page puts the position in one line, that the workflow runs itself while the judgment stays human. The page does not say what happens after an output is found to be wrong. Default modes are not described, because the customer configures the guardrails rather than receiving them preset.

Conga's customer story library carries dated, named accounts. The one about Conga CLM describes Cotality, formerly CoreLogic, improving its client service with Conga CLM, and is dated 5 September 2024. It carries no figure. Two other dated stories, DigiKey on price management and Kalixia at 160 times faster document generation, concern other Conga products. Customer logos on the product and pricing pages include Southwest Airlines, LinkedIn, AXA, Peloton, Cotality, T-Mobile, Adobe, Box and Kraft Heinz. The figures Conga publishes sit apart from any named customer. A 9 percent revenue increase appears beside the logo strip with no stated basis, and the features page claims 50 percent less review time with AI. Three headline counters on the product page display as zeros. Conga also cites G2 Leader recognition across five grids.

Leah publishes qualitative quotes from four named people. Noelle Perkins is EVP and Chief Legal Officer at Cushman and Wakefield, and Lidia Kamleh is Chief Legal Officer at Dubai Future Foundation. Frances Bain-Cumberbatch is Chief Legal and External Affairs Officer at Ansa McAL, and Zillia Knight is Senior Legal Officer at Terumo Europe. Three results are published with the customer unnamed. A major American logistics company cut contract review time by 91 percent. A global manufacturer protected more than $18 million of revenue, and an American retail REIT tracked more than $2 million of savings. About 54 enterprise logos appear, including Philips, MUFG, Sandoz, Pernod Ricard, Alaska Airlines and Wood PLC. PwC and KPMG appear among them. PwC entered a commercial alliance in March 2024, and Epiq resells Leah in its Service Cloud. Integreon is quoted as an early adopter that resells it, and Pinsent Masons adopted it for managed legal services in July 2025. Partners and customers are shown together without distinction, and the Chief Product Officer of Execo, another services partner, is among the testimonials.

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. Conga's Master Services Agreement is a separate document.

Leah says customer contract data is never used to train models. The AI governance page treats data leaking into models the customer does not own as a failure it engineered out. It says zero data retention is the only acceptable answer, and that Leah enforces zero retention with OpenAI and Anthropic so they process data but never store it. Encryption is AES-256 at rest and TLS in transit, with keys in Azure Key Vault, rotated and reachable only through controlled service accounts. Role based access control is said to apply at every layer, and single tenant deployment is offered for customers with strict isolation needs. Leah sells to Fortune 500 legal departments, and none of this material addresses privilege or work product.

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. The function pages name the audience, and the marketing does not describe the product in advice terms. The published materials do not address how a supervising lawyer meets competence or oversight duties over AI drafted contract language. They do not say which buyer groups may use which capability, and state no jurisdictional limit. The product is marketed to sales and procurement users who generate contract positions in the same tenant as legal.

Leah publishes nothing on the line between a tool and legal advice. Its site carries no disclaimer of any kind and no ethics or professional responsibility page, and it names no bar or ethics guidance, including ABA Formal Opinion 512. The platform is sold to run legal work end to end across legal, procurement and finance teams. In the vendor's own framing, agents carry out commercial work in several steps without routing every decision through a person.

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. Conga publishes no results from that testing, whether a bias audit finding, an evaluation output, a model card or a statement about uneven performance across contract types.

A dedicated AI governance page names six failure modes the vendor says it engineered out. They include black box decisions that cannot be defended to a regulator or board, and compliance frameworks retrofitted after the fact. Against them the page sets three pillars and a loop of policy, execution and audit. Each action is logged with its rationale and governing policy, in records described as tamper resistant and immutable. The page also says every action is measured against benchmarks for accuracy, bias and outcome, and that accountability is structural rather than aspirational. It names no person or role accountable for model behavior and describes no testing before release. It gives no benchmark method or schedule and discloses no bias measurement result.

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 control is documented control by control. It includes 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. Conga publishes its subprocessor list, gives fifteen days' notice before adding a new one, grants a right to object with termination and refund, and stays liable for subprocessors' acts. Incident notice comes within 48 hours of Conga becoming aware, backed by a documented response plan with root cause analysis and a 24/7 security team. All of these terms are published and can be read before signing.

The AI governance page describes TLS in transit and AES-256 at rest. Encryption keys are managed in Azure Key Vault, rotated regularly and reachable only through tightly controlled service accounts. The page also lists multifactor authentication, secure API gateways, network segmentation, real time monitoring and a documented incident response plan. Audit logs are described as comprehensive, tamper resistant and immutable. For outside assurance, the vendor says an independent Managed Security Service Provider audits it every year and that it is penetration tested regularly.

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.

Section 16.5 of the Master Terms and Annexes sets a General Cap equal to fees paid or payable in the twelve months before the first incident. An Enhanced Cap of three times that applies to breaches of its security or data protection terms, meaning the security clause and the data processing addendum. Indemnities, intellectual property claims, breach of confidentiality and anything that cannot legally be limited are uncapped. Section 17.1 gives the customer an indemnity against third party intellectual property claims. Section 8.2 warrants that the service will perform materially as documented, with a thirty day fix period under 8.3 and termination with a refund if the fix fails. Annex A publishes uptime tiers of 99.00, 99.5 and 99.9 percent by support plan. A tier missed in three consecutive months, or in four months out of six, allows termination with a refund. Three limits apply. Breaches of confidentiality involving Customer Data fall outside the uncapped claim, so they stay capped and rise to the Enhanced Cap only where the security or data protection terms are also breached. The agreement gives no indemnity for AI output, such as inaccurate output, hallucination or training data provenance. Section 9.2 bars the customer from submitting Sensitive Data, including GDPR Article 9 categories, and the provider disclaims liability for it. These terms are version 3.0c. Version 4.0, dated 4 January 2026, changes only the trading name, according to the vendor.

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 vendor states that the platform edition connects to any CRM, ERP or procurement system. 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. Conga publishes a documentation site at documentation.conga.com, a developer hub at developer.conga.com and an integrations page. The product pages show no field mapping or sync direction, and the claim of connecting to any CRM or ERP describes reach without saying what data moves.

Leah names its integrations and describes each by function. They cover ERP platforms including SAP and NetSuite, procurement systems including Coupa, financial systems, identity providers including Okta, and existing contract lifecycle tools. DocuSign and Adobe Sign are built in for signing, and a Microsoft Word add in handles redlining. The vendor also describes how the integrations work. It says Leah connects and executes rather than copying data passively, and carries out work across connected systems through the orchestration layer. Leah has a dedicated integrations page, but publishes nothing on what syncs in which direction or what a customer must configure. No document management integration such as iManage or NetDocuments appears, which fits a product built for in house teams rather than law firms.

Conga publishes 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. Tenants are logically separated with dedicated encryption keys. 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 publishes no region list, does not say how a tenant's region is chosen, and does not distinguish processing location from storage. Content reaches Azure OpenAI, Google Cloud Vision, Amazon Textract and Zuva, and no published page states where that processing runs.

The standard deployment is shared. Single tenant deployment is available for customers with strict isolation requirements. The vendor also offers what it calls a dedicated zero trust private environment in Azure OpenAI Studio, described as fully isolating data from all other customers. Leah runs on Azure, with keys held in Azure Key Vault. On data residency the vendor says only that it supports the residency and regulatory needs typical of large multinational enterprises. It names no region or jurisdiction and describes no customer choice.

Conga's trust center is ungated, linked from the site navigation, and names each standard. SOC 2 Type II is stated to cover the full platform and is audited annually. 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. That certification can be verified independently, because the Data Processing Addendum points to the public Department of Commerce list. The security program behind the standards is documented. It 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. No auditor, report period, observation window or certificate number is published for any standard, and the trust center holds no report. 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.

The AI governance page claims SOC 1 Type I and II, SOC 2 Type I and II, GDPR compliance, CCPA compliance, HIPAA readiness and ISO 27001 alignment. The home page FAQ, on the same site, says only that Leah is SOC 2 Type II certified, so the two pages disagree on what is held. For ISO 27001 and HIPAA the governance page says aligned and ready rather than certified. The auditor is described only as an independent Managed Security Service Provider, a category rather than a named firm. No coverage period, report date or audit scope is given. Penetration testing is said to be regular, with no partner named and no summary published. Leah has no trust center or portal, so there is no published route to request a report.

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.

The DPA Setup Page lists four model providers against Leah Functionality, each noted as storing or retaining no customer data and each with named jurisdictions. Anthropic PBC is listed for the USA, Japan, and the EU or UK, and OpenAI LLC for the USA, Japan, and the EU or Switzerland. Cohere Inc. is listed for Canada, the USA, the EU or UK, and Japan. Google AI/ML with Google Cloud is listed for the USA, Japan, and the EU, Switzerland or UK. Microsoft Azure Services is listed for hosting and translation, and the private deployment option runs in Azure OpenAI Studio. DPA clause 4.3 requires any new subprocessor to be added to the published list with at least thirty days' notice before it processes customer personal data. Clause 4.4 gives a thirty day objection right on reasonable data protection grounds. If the objection is not resolved, the affected order can be terminated with a refund of prepaid unused fees. No model or version is named for any provider. The platform is described as choosing among several language models for each task and letting customers extend or customize models. Nothing published shows which provider handled a given piece of work.

Conga's pricing page is linked from the main navigation and carries no price, band, term, tier table, unit of charge or minimum. It does not say whether the product is licensed per user, per contract or per platform, or what implementation adds. The page holds a heading, a paragraph saying every business is unique and a list of six things the pricing is said to prioritize, one of them Transparency. Below those sit two strips of customer logos and a quote request form. The nearest thing to a tier is a line on the platform page inviting buyers to add CLM Advanced features such as a clause library, version control and redlining. That line names an upgrade, not a price. The pricing and platform pages state no payment terms, renewal terms, price increase caps or termination rights. Conga's Master Services Agreement is a separate document.

Leah publishes no pricing at any level, including the unit of charge. The primary navigation covers platform, solutions, resources and company, and neither it nor the footer sitemap has a pricing page. There is no tier structure, no unit per seat, contract or agent, no volume banding and no indication of what implementation adds. Every call to action across the site is to request a demo. An implementation FAQ says timelines vary with scope and integrations and that a detailed plan is built during evaluation. It says nothing about cost. No published page gives a view of price before a sales process.

The site has a navigation tier for seven named functions, Legal, Procurement, Sales, Finance, IT, Business Operations and Pricing, each with its own page. The CLM material gives legal, sales and procurement different task lists. 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. Seven industry pages 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. The pages do not say which capabilities a user who is not a lawyer can reach in a shared tenant. They give no jurisdiction or language coverage statement, although the product is localized into German and French.

Leah publishes dedicated industry pages for CPG and manufacturing, energy and utilities, financial services, healthcare, and pharma and medical devices. It describes its customers as Fortune 500 enterprises in regulated industries. By function it publishes pages for legal leadership, legal operations, sales and revenue, procurement, and finance. The pages carry distinct propositions written for the General Counsel, the contract operations team, the Chief Procurement Officer and the finance leader. The customer roster spans banking, airlines, pharmaceuticals, consumer goods and engineering. No published page says which practice areas, contract types or matters the platform does not support, and none addresses smaller organizations. Law firms appear only indirectly, through managed service partners, rather than as a served segment.