Leah vs Summize: how they compare in 2026

L
Leah profile
S
Summize profile
Last verifiedOctober 8, 2026

Both of these come from Britain and both put agents on top of contract work, but they bring the AI to different people. Summize puts contract answers where the business already works. Its SIA agents answer questions inside Outlook, Teams, Slack and Salesforce, drawing on legal's own playbooks, so a salesperson can check renewal terms without leaving Salesforce. Leah's agents carry contracting, procurement and finance work for large enterprises under a governance loop the customer configures. Both publish their agreements, and both set a higher cap for security breaches. Summize sets its caps as the greater of a fixed sum or a multiple of charges, warrants the software free of material errors, and limits renewal price rises to 10 percent. Leah publishes uptime tiers and notice before a compelled disclosure, and Summize's agreement gives neither. Leah names four model providers and publishes its subprocessors. Summize names OpenAI and says SIA is built on Azure, and the subprocessor appendix its agreement cites is not published. On training, Summize's terms allow its own machine learning on anonymized customer data, while Leah says customer contracts never train models.

At a glance

Category
LeahContract Review & Drafting
SummizeContract Review & Drafting
Founded
Leah2012
Summize2018
Headquarters
LeahLondon, United Kingdom
SummizeManchester, United Kingdom
Last verified
LeahOct 8, 2026
SummizeOct 8, 2026

All 15 axes, side by side

The same grid applied to every vendor in the index, graded from public sources. Hover a grade to see what the letter means on that axis.

AI Centrality

How much of the product is actually AI. Whether the machine learning is the mechanism the buyer is paying for or a feature layered onto conventional software, and whether the vendor is specific about which is which.

Leah
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.

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.

Summize
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.

Summize describes its product as three layers, and only the third is AI. A Knowledge Layer holds playbooks and policies. A Contract Operations Layer runs the lifecycle from first request to signature inside existing tools. The agentic AI layer, SIA, is described as surfacing that knowledge as instant answers. Without SIA, a working contract request, repository and operations system remains, embedded in Outlook, Teams, Slack and Salesforce. Summize presents the layers as distinct, each one powering the next.

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.

Leah
CC on Citation Accuracy and Hallucination DisclosureAccuracy is asserted without measurement, or grounding is claimed while output cites sources the reader cannot open and verify.

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.

Summize
CC on Citation Accuracy and Hallucination DisclosureAccuracy is asserted without measurement, or grounding is claimed while output cites sources the reader cannot open and verify.

SIA is described as giving instant, reliable answers grounded in the customer's own knowledge and standards. That identifies the grounding source as the Knowledge Layer of playbooks and policies, but no retrieval method is described behind it. The security page says Summize evaluates the effectiveness, quality and security of its AI models on a consistent basis. No result, test set, cadence or scope is published for those evaluations. Summize publishes no accuracy figure. Its materials do not discuss hallucination or name a failure mode, and the published performance figures all measure speed and volume rather than correctness.

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.

Leah
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.

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.

Summize
CC on Autonomy and Oversight ModelAutonomy is claimed and oversight is asserted without a mechanism. Human in the loop appears as a phrase rather than a described control.

Summize says the business becomes more self sufficient while legal remains in full control. It says questions that used to reach legal's inbox are answered instantly by the people who needed them. Its materials do not say what SIA answers alone and what a lawyer approves, and they state no threshold. No review screen is described, and nothing covers what happens when an answer is wrong. Apart from the line that legal remains in full control, Summize describes no oversight arrangement.

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.

Leah
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.

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.

Summize
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.

Three named customers give attributed quotes. Steven McGeagh at Huel speaks to ease of adoption, Julia Trius at Edpuzzle to receiving agreements already in the required format, and Derek Ihnen at Boon Edam to reduced review time. Customer logos include Revolut, SeatGeek, Miami Heat, Matillion, Sigma Computing, CodeRabbit, KSE and IPC Systems. Summize cites three times faster contract creation, a 40 percent reduction in deal length, a 50 percent reduction in processing time and six times more contracts reviewed. It puts an NDA at two minutes against two hours. A 4,062 percent ROI is attributed to Nucleus Research, a named analyst firm. None of these figures is tied to a named customer or dated. Huel, Edpuzzle and Boon Edam each also have a case study page.

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.

Leah
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.

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.

Summize
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.

Under clause 6.1 of the SaaS terms, Summize may store, transmit and process Customer Data only as needed to provide the services, and gets no other rights in it. Clause 6.2 requires physical, technical and organizational measures in line with good industry practice. Clause 6.5 imposes confidentiality with named exceptions. Clause 6.6 requires daily encrypted backups available to the customer on request, and clause 9.2 requires prompt deletion or return of all Customer Data at the customer's choice on termination. Summize says prompts, completions, embeddings and training data are exclusive to each customer and not available to OpenAI or used to improve OpenAI models. Clause 6.4 reserves the right to use Customer Data in aggregated, anonymized form to improve the software through machine learning, so the agreement permits training. Separation between customers is described as siloed AI, without detail on how it is enforced. Summize's published materials do not address privilege or work product.

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.

Leah
DD on UPL and Professional Responsibility PostureNothing published on the advice line for a product that produces legal work, including where it is sold to people who are not lawyers.

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.

Summize
DD on UPL and Professional Responsibility PostureNothing published on the advice line for a product that produces legal work, including where it is sold to people who are not lawyers.

Summize markets contract answers to people who are not lawyers, in sales, finance, HR and procurement teams. It says questions that used to reach legal's inbox are taken care of, giving the examples of a salesperson checking renewal terms and a CFO querying payment performance without involving legal. Its materials do not say what the output is and is not, and no disclaimer separates information from legal advice. There is no competence or supervision language, and no jurisdiction limit is stated, although customers are in the UK and the US. The SaaS terms contain warranties, indemnities and liability caps but no provision on legal advice. The website terms of use disclaim only the website. The marketing line that legal remains in full control describes workflow, not advice.

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.

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

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.

Summize
CC on AI Governance and Bias DisclosureResponsible AI principles are published without a mechanism, a testing regime, or anything a buyer could audit.

The security page sets out four AI commitments, each in one sentence: siloed AI practices, regular assessments of effectiveness, quality and security, ongoing updates to AI capabilities, and a customer feedback loop. No one at Summize is named as accountable for AI outcomes. No testing regime before release is described, and no assessment result is published. Nothing addresses bias or uneven output across contract types or counterparties. The company's General Counsel has written an explainer on the EU AI Act, which comments on the regulation rather than describing Summize's own governance. ISO 27001 is an information security standard and does not cover AI governance.

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.

Leah
BB on AI Safety and Data StewardshipSubstantive published policy covering most of the ground, short of the full set: commonly no named subprocessor list or no stated incident practice.

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.

Summize
BB on AI Safety and Data StewardshipSubstantive published policy covering most of the ground, short of the full set: commonly no named subprocessor list or no stated incident practice.

On termination, clause 9.2 of the SaaS terms requires Summize to promptly delete or return all Customer Data at the customer's option. Retention after that is allowed only where law requires, and confidentiality obligations continue over anything retained. Clause 6.6 requires backups no less frequently than daily, secure and encrypted, in a commonly used machine readable format and available to the customer on request. Access control rests on ISO 27001, with DevSecOps practices and internal password, equipment and data confidentiality policies described. Clause 3.2 gives an annual audit right over user and password compliance. Summize states that it runs regular third party penetration testing. The agreement sets no retention period for the term itself, only for its end. No subprocessor list is published. Clause 8.4 refers to Appendix 3 as defining Sub-Processors, but the appendix is not included in the published document.

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.

Leah
AA on AI Liability and RecourseWhat the vendor stands behind when its output is wrong is published and specific: indemnity scope, caps, carve outs, and any insurance or warranty a buyer can actually invoke.

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.

Summize
AA on AI Liability and RecourseWhat the vendor stands behind when its output is wrong is published and specific: indemnity scope, caps, carve outs, and any insurance or warranty a buyer can actually invoke.

The SaaS terms give the customer an intellectual property infringement indemnity in clause 7.2, covering claims, liabilities, losses, damages and reasonable costs. Clause 7.3 sets one named carve out, for unapproved combinations. Under clause 7.4, which sets out how claims are handled, Summize may not settle without unconditionally releasing the customer. Each liability cap is the greater of a fixed sum or a multiple of charges, so the fixed sum sets a minimum. Clause 8.3 caps general liability at the greater of £100,000 or 150 percent of total charges. Clause 8.2 sets a separate, higher cap for breach of the security and data protection obligations, at the greater of £500,000 or 500 percent of total charges. Clause 8.1 preserves liability for willful misconduct, and clause 8.4 makes Summize liable for its subcontractors and subprocessors as for itself. Clause 3.6 warrants that the software meets its specification in all material respects and is free of material errors and defects. Clause 3.5 requires reasonable skill and care, clause 3.8 warrants against malicious code, and clause 7.1 warrants that Summize holds the rights to supply the service. The agreement does not disclaim output accuracy, and Summize publishes no insurance position.

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.

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

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.

Summize
AA on Practice Systems Integration DepthDocumented, verifiable integrations into the systems legal work already lives in, with the depth described: what syncs, in which direction, and what a firm must configure.

Summize works inside Outlook, Microsoft Teams, Slack, Gmail, Microsoft Word, Salesforce, HubSpot and Jira. It adds Summize Sign for e signature and a Claude integration, and each integration has its own dedicated page. The examples given are a salesperson checking renewal terms inside Salesforce and a CFO querying payment performance across the supplier base. Contract context and assistance are available in the tool, without a new login to manage. Summize says there is no separate platform to adopt. Implementation runs in sprints of three to four weeks under a methodology Summize calls HERO, with in house implementation staff. A full rollout typically completes within twelve weeks.

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.

Leah
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.

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.

Summize
CC on Deployment Model and Data ResidencyCloud delivery is implied and neither the tenancy model nor the region is stated.

On its home page Summize says data never leaves the customer's environment, and its FAQ says the platform is built on Azure enterprise infrastructure. That names the infrastructure provider, but no region is given and nothing says where customer contract data is stored. The only published hosting location is in the website terms of use, which say the Website is hosted on servers in the United Kingdom. That covers the marketing site, not the software. Summize does not say whether the platform is single tenant or multitenant. Siloed AI, as Summize describes it, covers how prompts and embeddings are handled rather than a tenancy model.

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.

Leah
CC on Security Certifications and Trust CenterBadges appear on the site with no scope, no date, and no report available.

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.

Summize
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.

Summize holds ISO 27001 certification, and its badge names ISOQAR as the certification body and UKAS as the accrediting body. No certificate number, scope, statement of applicability, or issue and expiry dates are published, and there is no trust portal or route to a report. Penetration testing is described as regular and third party, with no firm or dates named. A security whitepaper by CTO Richard Somerfield is offered behind a form. Summize does not hold SOC 2. It says it audits infrastructure in line with standards including SOC II and intends to work toward SOC II accreditation.

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.

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

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.

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

The security page names OpenAI and states that customer prompts, completions, embeddings and training data are not available to OpenAI or used to improve OpenAI models. The FAQ adds that SIA is built on Azure enterprise infrastructure. No specific model or version is named, and Summize publishes no commitment to notify customers when a model or provider changes. No subprocessor register is published. Appendix 3, cited in the agreement as defining Sub-Processors, does not appear in the published text.

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.

Leah
DD on Commercial TransparencyNo pricing information published at any level, including the unit of charge.

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.

Summize
BB on Commercial TransparencyReal pricing is published for part of the range, with enterprise tiers withheld, or the unit and structure are stated without the figure.

Summize sets out its pricing structure in its published SaaS terms, and its site has no pricing page. The terms define the Order Form as setting out user numbers and the type of software license, so the charge is per user by license type. The initial term renews automatically for twelve month periods unless 90 days' written notice is given. Clause 2.2(b) limits any renewal increase to 10 percent over the previous twelve month term for the same plan, tier and package, unless a higher cap is agreed. Payment is due 30 days from a valid invoice. Fees exclude VAT and sales tax but include other taxes, and expenses need prior written approval. No figure, band, tier name or feature split is published.

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.

Leah
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.

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.

Summize
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.

Summize has a dedicated page for each of five buying teams (Legal, Sales, Finance, HR and Procurement) and for each of eight sectors. The sectors are Software, Sports, Finance, Manufacturing, Business Services, Media and Internet, Retail and Telecommunications. Four use cases are published as request, review, repository and analytics. NDAs are named as a specific contract type with a stated handling time. The buyer is a corporate in house function rather than a law firm, and law firms are neither claimed nor excluded. No organization size is stated, and no contract types beyond NDAs are listed as supported. Government use is not addressed, and nothing says where the product stops.

The 12 legal signals, side by side

Recorded rather than graded. These are the questions a practitioner has to answer before a tool touches a client matter, and the answers are taken from public material only.

Client Data in Training

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

Leah
Never, in policy only

Leah's security FAQ, on its home page, 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 enforced so that OpenAI and Anthropic process data but never store it. No term in the Master Terms and Annexes v3.0c names training, model training, machine learning or model improvement for customer content, either way.

Two clauses come close. Clause 5.1 limits the provider's use of Customer Data to providing and maintaining the Cloud Service, Support and Professional Services. Clause 5.4 allows use of Usage Data, the provider's technical logs, data and learnings about the customer's use, to run, improve and support the service. Usage Data excludes Customer Data, so the improvement right covers telemetry, not content. Together the clauses fit a ban on training without stating one.

They leave open whether model improvement counts as maintaining the service. The commitment rests on the published policy, not a contract term. Version 4.0 of January 2026 changes only the trading name, according to the vendor.

Summize
Permitted, in the contract

Clause 6.4 of the published SaaS terms reserves Summize's right to use Customer Data in aggregated, anonymized form to improve the Services or Software through automated decision processing or machine learning analysis. The clause applies despite the security and data protection clauses before it. It names machine learning and applies to Customer Data, and the anonymization qualifier does not remove the permission. The marketing statements concern outside models.

The home page promises a contractual guarantee that data is never used to train external models. The security page says prompts, completions, embeddings and training data are not available to OpenAI or used to improve OpenAI models. Clause 6.4, by contrast, permits Summize's own machine learning on aggregated, anonymized Customer Data. The marketing does not mention clause 6.4, and the clause does not carry the commitment on outside models.

Prompt and Output Retention

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

Leah
Disclosed fixed window

Section 14.4 allows export during the subscription and deletion of Customer Data within sixty days of a request after termination. That is subject to standard backup or record retention policies and legal requirements, and the customer cannot change the period. The data processing addendum adds secure deletion to industry standards at clause 8.2, with a certificate of deletion on request. Schedule 1 commits to export in CSV or a similar format within thirty calendar days and to physical destruction of media by a recognized provider.

Prompts and outputs have no separate window. The agreement treats Customer Data as one class, defined at section 23 as any data, content or materials the customer submits, so prompts and outputs follow that regime. Usage Data sits outside it. Section 5.4 lets the provider collect Usage Data, meaning its technical logs, data and learnings about the customer's use, excluding Customer Data. The provider may use it to run, improve and support the service and for other lawful purposes such as benchmarking.

It may disclose Usage Data externally only if deidentified and aggregated across customers. No deletion duty applies to Usage Data, and section 14.5 makes 5.4 survive termination.

Summize
Disclosed without a period

Backups are covered by clause 6.6 of the published agreement. It requires Summize to perform and maintain backups of all Customer Data no less frequently than daily, secure and encrypted, in a commonly used machine readable format and available to the customer on request. Clause 9.2 covers the end of the relationship. It requires prompt deletion or return of all Customer Data at the customer's option on termination. Retention after that is permitted only where and for as long as law requires, and confidentiality continues over anything retained.

The agreement does not state how long prompts, outputs or uploaded contracts are held during the term, and Summize describes no configurable retention window.

Ethical Walls and Matter Segregation

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

Leah
Claimed, not documented

Leah describes separation at the customer level, through deployment options. The vendor states that single tenant deployment is available for customers with strict data isolation requirements. It says a dedicated zero trust private environment within Azure OpenAI Studio ensures complete isolation from all other customers. Role based access control is stated to be enforced at every layer. That wording makes isolation a deployment option rather than the default, and nothing published describes how customers are separated in the standard shared deployment.

Legal, procurement, finance and shared services teams work in the same system, and nothing published addresses boundaries between them inside a customer.

Summize
Claimed, not documented

The security page describes siloed AI practices under which customer prompts, completions, embeddings and training data are available exclusively to that customer and not to other customers. The home page FAQ repeats this as a siloed AI approach that keeps each customer's prompts, data and outputs exclusive to them. Summize does not describe the isolation mechanism or the tenancy model. Beyond the agreement's user and password provisions, nothing says how access is administered. Nothing addresses separation between matters or contract sets inside a single customer.

Third Party Request and Subpoena Notice

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

Leah
Notice committed

Section 19, headed Required Disclosures, lets the recipient disclose Confidential Information where the law requires. Where the law permits, the recipient must give advance notice and reasonable cooperation, at the discloser's expense, to obtain confidential treatment. The clause expressly covers Confidential Information including Customer Data. Section 23 confirms that the customer's Confidential Information includes Customer Data, so customer material sits inside the notice duty.

The duty is mutual and binds whichever party receives the demand. Section 14.5 makes section 19 survive termination. Leah publishes no transparency report, so there is no public count of demands received or of how they were answered. These terms are version 3.0c. Version 4.0 of January 2026 changes only the trading name, according to the vendor.

Summize
Disclosure addressed, notice absent

Clause 6.5 of the SaaS terms requires both parties to keep the other's confidential information, expressly including Customer Data, confidential. Disclosure to a third party is allowed only if required by law or regulation, permitted in writing, or if the information has become public without default. The clause therefore covers compelled disclosure directly. The SaaS terms do not commit Summize to notify the customer of such a request, and reserve no discretion over notice either.

The agreement says a separate confidentiality agreement, if the parties have one, takes precedence over clause 6.5. Summize publishes no such template.

Primary Law Corpus Provenance

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

Leah
Sources named, basis unstated

Leah works on the customer's own material. The vendor states that Leah operates against the customer's policies and playbooks and gains intelligence from the customer's unstructured data and business rules. It answers contract questions from the customer's repository with sources attached. The vendor also refers to Leah operating against established legal precedents, but names no source, jurisdiction, database or rights basis for them.

The product manages a customer's contracts rather than retrieving primary law. No provenance statement backs the precedent reference, and no update cadence is published for anything.

Summize
Not addressed

Summize grounds its answers in the customer's own Knowledge Layer of playbooks and policies and in that customer's contract repository, rather than retrieving primary law. It identifies no external corpus and names no external database, publisher or content license. No jurisdictional coverage is claimed.

Good Law Verification

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

Leah
Not addressed

Leah describes no citator, treatment signal or currency check, and does not say whether legal authority is reviewed for later history. The platform manages contracts, obligations and procurement workflows rather than retrieving case law, so a citator is not part of what it sells. The vendor does refer to Leah operating against established legal precedents, without identifying any source. That is the one place the product invokes primary authority, and no verification step is described for it.

Summize
Not addressed

Summize does not retrieve primary law. It works on the customer's own contracts, playbooks and policies to answer contract questions and run the contract lifecycle. Checking authority for subsequent history does not arise for a product of this kind, and Summize publishes nothing on it.

Refusal and Uncertainty Behavior

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

Leah
Not addressed

The home page and the AI governance page describe no explicit path for Leah to decline to answer or abstain, and no confidence or grounding rating. The governance loop does produce rejections. Approvals, escalations and rejections are applied automatically according to the customer's rules. Those are policy outcomes set by configured guardrails, not the model declining because it cannot ground a response. Neither page says what Leah does when the customer's own contract set or playbook does not cover the question in front of it.

Summize
Not addressed

SIA is described as giving instant, reliable answers grounded in the customer's own knowledge and standards, a claim about the normal case rather than the failure case. Summize does not say what the product does when it cannot ground an answer. It describes no abstention path, no behavior for when no answer is available, and no confidence or grounding measure shown to the user. Its materials, the dedicated security page included, do not discuss hallucination.

Fabricated Citation Record

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

Leah
None located

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 Leah or the former company name ContractPodAi. Published 2026 sanctions trackers and trade press summaries name neither. The platform runs commercial contracting and procurement work rather than producing court filings, so its output does not ordinarily reach a brief.

Summize
None located

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 Summize. Summize is a corporate contract intelligence system rather than a litigation tool.

Bar Guidance Alignment

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

Leah
Not addressed

Leah publishes nothing that engages with bar or ethics guidance. That includes ABA Formal Opinion 512, state bar guidance in the United States, and Solicitors Regulation Authority or Law Society material. The company is headquartered in London and sells into legal departments across North America, Europe, Asia and Australia. Its published compliance material covers regulation and security frameworks, namely GDPR, CCPA, HIPAA, SOC and ISO. None of it addresses the professional conduct obligations that bind the lawyers using the product.

Summize
Not addressed

Summize publishes an explainer on the EU AI Act by its General Counsel. It comments on the regulation and does not engage with bar or ethics guidance about Summize's own product. Its site and terms name no bar association, law society, regulator or ethics opinion. The buyer is a corporate in house function rather than a regulated practitioner in private practice.

Billing and Fee Posture

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

Leah
Savings claims only

Leah frames its public materials around cost and time removed, quantified at portfolio level. It cites a 91 percent cut in contract review time, more than $18 million of revenue protected and more than $2 million of tracked savings. Its headline figures are more than $125 billion of commercial value managed and more than $10 billion of ROI impact delivered. No per matter record of AI assisted work for fee purposes is described, and no guidance on billing, fee or client disclosure treatment is published.

The vendor describes an immutable audit log of every action, which could in principle support such a record, but does not present it for that purpose. Leah sells to in house functions rather than firms billing clients, so the costs in play are internal cost and outside counsel spend. Its materials address neither.

Summize
Savings claims only

Summize claims time and cost savings. It cites three times faster contract creation, a 40 percent reduction in deal length, a 50 percent reduction in processing time, six times more contracts reviewed, and two minutes against two hours for an NDA. It attributes a 4,062 percent return on investment to Nucleus Research. Its materials do not address billing or disclosure, including what happens to a bill when AI assisted work takes less time.

No record of AI assisted work by matter is described. The buyer is an in house department rather than a firm billing a client.

Outside Counsel Guideline Readiness

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

Leah
Subprocessors listed

The data processing agreement is Annex B of the Master Terms and Annexes v3.0c. The DPA Setup Page lists every subprocessor with its purpose, location and the product it serves. The list names ABBYY OCR SDK, Anthropic PBC, Cohere Inc., DocuSign or Adobe, Google AI/ML and Google Cloud, Jitterbit, Microsoft Azure Services, OpenAI LLC, QlikTech, Sendgrid, ZOHO, Zuva and four ContractPod group entities. Anthropic, OpenAI, Cohere and Google AI/ML are each listed against Leah Functionality as model providers, noted as storing or retaining no Customer Data, with named jurisdictions.

The DPA itself is the Bonterms DPA, published openly in the same PDF and ready to forward. It incorporates EU Standard Contractual Clauses Modules 2 and 3 and the UK International Data Transfer Addendum. It sets out processing details in Schedule 1 and fixes a 48 hour notice period for security incidents. Clause 4.3 commits to listing any new subprocessor and giving at least 30 days' notice before it processes anything.

Clause 4.4 gives an objection right, with termination and a refund if the objection is not resolved. Version 4.0 of January 2026 changes only the trading name, according to the vendor.

Summize
Subprocessors listed

The public security page names OpenAI as a model provider and says customer prompts, completions, embeddings and training data are not available to OpenAI or used to improve OpenAI models. The home page FAQ adds that the system runs on Azure. Together they say who handles customer content, without a sales conversation. No subprocessor register or forwardable pack for clients is published. Clause 8.4 of the SaaS terms cites Appendix 3 as defining Sub-Processors, but the appendix does not appear in the published document. Summize publishes no data processing agreement, and its security whitepaper sits behind a form.

Court Disclosure Support

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

Leah
Partial record

The audit stage of Leah's published governance loop logs every decision. Each entry records what the agent did, why, under which policy, with what data and with what outcome. The records are described as tamper resistant, immutable and ready for any audit. That gives the action, the rule, the inputs and the result for each action. The published description of the log does not include the model. The platform chooses among several language models for each task and identifies no model or version, so the log does not show which system produced a given passage.

No export built for court disclosure or AI use certification is described. The audit framing is regulatory and internal rather than judicial.

Summize
Not addressed

Summize publishes nothing on court disclosure or verification certification. Its materials describe no audit trail or activity export, do not disclose to the customer the model behind a given answer, and mention no record of human verification. The product is a corporate contract intelligence system rather than a litigation tool.

What neither one publishes

The questions both sides leave open

Derived from the records above rather than written, so it cannot favor either vendor. Take these into both conversations and ask each side the same question.

Axes where neither earns credit
  • UPL and Professional Responsibility Posture
Signals neither addresses in public material
  • Good Law Verification
  • Refusal and Uncertainty Behavior
  • Bar Guidance Alignment

Which one fits

Choose Leah if

  • You need the AI supply chain on paper. Leah's subprocessor list names Anthropic, OpenAI, Cohere and Google with their jurisdictions. Its data processing terms give thirty days' notice and an objection right before a new subprocessor starts.
  • You want to be told about compelled disclosure. Section 19 of Leah's master terms requires advance notice and cooperation before customer data is disclosed under legal compulsion, where the law permits. The duty survives termination.
  • You want agents doing work, not only answering questions. Leah's agents carry contracting, procurement and finance tasks under permissions and escalation points the customer sets. Every action is logged against its rationale and policy.

Choose Summize if

  • You want answers inside the tools people already use. Summize runs in Outlook, Teams, Slack, Word and Salesforce. A salesperson can check renewal terms in Salesforce, and a request can be raised from Teams.
  • You are a smaller buyer who wants meaningful caps. Summize caps general liability at the greater of £100,000 or 150 percent of charges. For security and data protection breaches the cap is the greater of £500,000 or 500 percent.
  • You want price rises limited in writing. Summize caps any renewal increase at 10 percent for the same plan. Contracts renew yearly with 90 days' notice to leave, and rollout typically finishes within twelve weeks.

In summary

Leah

Leah, formerly ContractPodAi, is a product of ContractPod Technologies Limited of London. It runs contracting, legal, procurement and finance work at large enterprises on top of a contract lifecycle product with intake, review in Word against playbooks, approvals, signing and a repository. The AI Legal Index records a governance model and a paper trail that are both published. Customers set agent permissions and escalation, and every action is logged with its rationale. Leah's master terms set liability caps, a sixty day deletion window and notice of compelled disclosure. Its subprocessor list names Anthropic, OpenAI, Cohere and Google. It publishes no price, accuracy figure or position on legal advice.

Source: AI Legal Index, 2026

Summize

Summize is a contract intelligence system for in house legal teams that works inside the tools a business already uses, including Outlook, Teams, Slack and Salesforce. It has three layers. A Knowledge Layer holds playbooks and policies, a Contract Operations Layer runs requests through to signature, and its SIA agents answer contract questions across the business. According to the AI Legal Index, Summize's subscription agreement is specific. It gives an intellectual property indemnity, a warranty against material defects and liability caps with fixed floors of £100,000 and £500,000. Renewal price rises are capped at 10 percent. It holds an accredited ISO 27001 certificate. Its terms allow anonymized customer data to improve its software through machine learning.

Source: AI Legal Index, 2026

Questions buyers ask

Leah vs Summize: which is better for an in house legal team?

It depends who needs the answers. Summize brings contract answers to the rest of the business inside Salesforce, Slack, Teams or Outlook, under terms with fixed liability floors and a renewal price cap. Leah runs agents through contracting, procurement and finance work at large enterprises, with its model providers and subprocessors published. From the AI Legal Index, based on each vendor's own published materials as of October 8, 2026. No vendor pays for placement.

Do Leah and Summize train AI on customer contracts?

Summize says prompts, completions and embeddings are not available to OpenAI or used to improve its models. Clause 6.4 of its agreement still lets Summize use anonymized, aggregated customer data to improve its own software through machine learning. Leah says customer contract data is never used to train models, and holds OpenAI and Anthropic to zero retention. From the AI Legal Index, based on each vendor's own published materials as of October 8, 2026. No vendor pays for placement.

Which AI models do Leah and Summize use?

Summize names OpenAI and says SIA is built on Azure, without naming a model or version or publishing a subprocessor register. Leah names Anthropic, OpenAI, Cohere and Google on a published subprocessor list, with jurisdictions but no versions. Leah also commits to notice before changes. From the AI Legal Index, based on each vendor's own published materials as of October 8, 2026. No vendor pays for placement.

What security certifications do Leah and Summize hold?

Summize holds ISO 27001 from ISOQAR under UKAS accreditation, which can be checked on a public register, and says it intends to work toward SOC 2. Leah's governance page lists SOC 1, SOC 2, ISO 27001 alignment and HIPAA readiness. Its home page says only SOC 2 Type II, and no auditor is named. From the AI Legal Index, based on each vendor's own published materials as of October 8, 2026. No vendor pays for placement.

What do Leah and Summize both leave unpublished?

Neither publishes a price figure, an accuracy or hallucination measure, or anything on attorney client privilege. Neither says where its answers stop short of legal advice, though both put AI answers in front of sales, finance and procurement staff. Neither names a hosting region for customer data. From the AI Legal Index, based on each vendor's own published materials as of October 8, 2026. No vendor pays for placement.

Disclosure

Neither vendor paid for inclusion, placement or a grade, and neither reviewed this page before it published. Everything on it comes from public material on the dates shown. How the index grades.

Summize's paperwork reads two ways on training. Its security page says prompts, completions and embeddings are not available to OpenAI or used to improve OpenAI models. Clause 6.4 of its agreement lets Summize use anonymized, aggregated customer data to improve its own software through machine learning. The subprocessor appendix its agreement cites is not in the published document. Leah's no training promise is a policy rather than a contract term. Neither vendor reviewed this page.

Contact

Correct a record, or ask how something was graded

Every grade and every signal on this index is drawn from public sources and dated. If a record is wrong, out of date, or missing an artifact the index did not locate, send the source and it will be reviewed and the record redated. Vendors are welcome to submit documentation. Nothing on this index is for sale, including a listing, a placement, or a grade.

AI Legal Index

The AI Legal Index is an independent index that tracks changes to AI vendors in legal. It holds 303 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 8, 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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