GC AI vs LegalOn: how they compare in 2026
The difference between LegalOn and GC AI starts with who writes the playbook. LegalOn ships more than 135 playbooks written by its own attorneys, covering about 10,000 legal issues across contract types and dozens of countries, and keeps them current as law changes. Its agents handle intake, review, playbook generation, translation and drafting. On the fullest plan, an Intake Agent completes and screens requests from email, Slack or a form, and a Triage Agent approves standard agreements. GC AI starts from the team's own positions, with four ready made playbooks and a builder that turns a team's templates into new ones. It also answers business questions in chat with cited research and acts in email, Slack and CRM through Agent Connectors. Both publish benchmarks of their own output. GC AI lists a $500 seat, while LegalOn's plans are priced after a demo. Attorney written standards on day one favor LegalOn, and a week that runs well beyond contracts favors GC AI.
At a glance
All 15 axes, side by side
The same grid applied to every vendor in the index, graded from public sources. Hover a grade to see what the letter means on that axis.
AI Centrality
How much of the product is actually AI. Whether the machine learning is the mechanism the buyer is paying for or a feature layered onto conventional software, and whether the vendor is specific about which is which.
Chat answers questions and drafts documents, playbooks run first pass contract reviews, and Contract Intelligence extracts and reconciles terms across a whole portfolio. The Word add in redlines selected clauses or entire agreements, Automations rerun saved instructions on a schedule, and Easy Prompt rewrites a plain request into a detailed legal prompt before it runs. Chats can also draft and send email, build PowerPoint decks and bring earlier conversations back into a new one on request. Requests route across models from Anthropic, OpenAI, Google and xAI, with automatic fallback to another provider when one fails. Complex tasks run through a five step reasoning sequence of scoping, systematic review, pattern tracing, completeness accounting and reconciliation. Cohere's embedding model handles retrieval over uploaded files, and GC AI describes a 20,000 line system prompt tuned for concise, business focused answers. Files, projects, vaults and the skill library hold the material and instructions the models work from. Inside a project, each chat can read the project's files and its sibling chats.
Review reads a contract against each playbook guideline in turn and drafts redlines. Assistant answers questions about the open contract in Word or the browser, drafts fallback language and issues lists, and runs one click skills that extract terms, check definitions and summarize obligations. The Playbook Agent builds playbooks from a team's policies, templates and past redlines. The Intake Agent asks requesters follow up questions and routes a complete matter, classified by contract type, urgency, counterparty and deal value, and the Triage Agent screens low risk agreements against the playbook. Vault extracts key data, dates and obligations from the signed repository into a table a team can filter, and answers questions such as which contracts renew in the next 90 days. Translate pairs DeepL with LegalOn's own translation agent and sends back only the changes in the counterparty's language. All of it runs on models applied to playbook content that LegalOn's attorneys write.
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.
Answers carry numbered citations that open the source with the quoted passage highlighted, so a lawyer can read the exact text behind each statement. Exact Quote works across uploaded files, web research and the legal databases, and an exported chat can include a citations section listing each quote and its source file. More than 14 million federal and state opinions, supplied by Midpage AI, back the case law answers. Each cited case opens in full in an Opinion Reader, with treatment flags where later history exists. The International Law database links each authority to its official portal, shows how often later decisions cite a case and marks some statutes as in force or not. The Research Agent ranks primary law ahead of secondary sources and uses reference sites such as Wikipedia only for background, never as citations. On GC AI's own In-House Legal Bench of 100 in house tasks, published in May 2026, GC AI passed 86.8% of attorney written criteria, against 79.8% for ChatGPT, 68.4% for Claude and 57.5% for Gemini. Its widest margins came on legal research, regulatory tracking and checklists, and only example tasks and answer keys are released. GC AI tells Word add in users to double check output because hallucinations and errors can occur.
Review grounds each issue in a playbook standard written by LegalOn's attorneys or by the customer, with the guidance and sample clauses behind it. Each guideline runs as its own check against the contract, about two dozen in parallel, rather than one pass over the whole document. The 2026 Contract Review Benchmark, released in June, set LegalOn against 11 general purpose AI systems across 3,282 pairwise reviews on 21 guidelines. An LLM judge, separate from the systems tested and blind to authorship, picked the more accurate, complete and useful review, and legal experts validated a sample of its outputs. LegalOn ranked first on all 21 provision types and finished a full review in 2.3 seconds. A downloadable report sets out four failure modes of general models on contract provisions.
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.
Agent Connectors split every app action into read tools and write tools. Reads default to Always allow, while writes and deletes default to Needs approval, so GC AI asks before an email goes out or a record changes. A member can set any tool to Always allow, Needs approval or Block, and each approval card offers Approve, Always approve or Deny, with the draft open for editing first. Admins set each connector to Disabled, Read only or Full access for everyone or for named members. Changes inside GC AI follow the same pattern. Creating, renaming, moving or deleting a project appears as a proposal to approve or deny, and files added from chat wait for approval. Contract Intelligence links an amendment to its parent agreement on its own only when the match is high confidence, and offers the rest as suggestions to confirm or dismiss. Any extracted value can be corrected by hand and later reverted to the AI value with its citations. Stakeholder seats give outside counsel and business partners a restricted vault chat. It answers factual questions about shared contracts and sends questions of legal or commercial judgment back to the legal team. Automations run unattended and deliver each result as a new chat for review, and the services agreement requires the customer to make sure users review output.
Routine paper moves on its own and judgment stays with the user. The Triage Agent screens low risk agreements against the playbook, approves the standard ones and escalates the exceptions, and the Intake Agent follows up with requesters until intake is complete. Every agent returns output for review, with legal setting the guardrails and keeping final approval. Review ranks each issue low, medium or high with the playbook guidance behind it, and redlines land as tracked changes a user accepts or rejects. One click AI Revise in Word works through the same tracked changes. Who sets the line between standard and nonstandard paper, and what happens after a wrong approval, is not described.
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.
Eight customer stories name both the company and the lawyer. Tipalti's senior director of corporate legal reports 609 hours saved year to date. Snyk's senior managing counsel says time on core legal tasks fell by half or more, and Interface's head of compliance estimates major tasks take about half the time. Helix's chief privacy officer says productivity doubled, and Jasper's head of commercial legal says tasks that took an hour now take ten minutes. Arc'teryx, Columbia Sportswear and Viant Technology describe how their teams use the product without figures. Viant's chief legal officer, for example, runs HR and privacy questions through GC AI before deciding whether to call outside counsel. Customer logos in the trust center include Vercel, Wayfair, Bass Pro Shops, Eventbrite and Post Holdings. More than 2,100 legal teams in 53 countries use the product by GC AI's count, over 200 of them public companies, and more than 12 million contracts have been reviewed. A December 2025 ROI study of more than 100 active customers reports 14 hours saved per lawyer each week and outside counsel spend down 14%, while GC AI's FAQ puts that cut at 30%. The story figures are the quoted lawyers' own accounts, and an unnamed Fortune 500 technology company is cited as saving 400 hours a month on NDA review.
Four customer stories pair a named company with figures. TriHealth, a Cincinnati health system whose legal team handles more than 1,500 contracts a year, cut review time by 75%. Its associate general counsel says clinical trial agreements that took hours now take about 20 minutes. Industrial Service Solutions saves its lead reviewer more than 15 hours a week and cut turnaround by 70%. Achievers, an HR technology company, reports NDA review time down 70% and $1,000 to $2,000 saved per third party contract. MCEA Holdings, a Japanese holding company, handles 50% more contracts without added headcount and resolves matters 20% faster. Each story names the speaker and role and sets out the starting point, such as a two week turnaround at Industrial Service Solutions and 15 to 20 minutes per NDA at Achievers. The site counts more than 9,000 customers.
Privilege and Confidentiality Posture
How client confidences are handled: attorney client privilege and work product treatment, segregation of one client matter from another, whether client data trains any model, and what the vendor commits to in writing rather than in marketing.
Section 4.9 of the services agreement bars GC AI from using customer data to train generative AI models, and section 5 binds both sides to confidentiality, with notice before any compelled disclosure. Customer data is logically separated from other customers' data, encrypted with AES-256 at rest and TLS 1.2 or higher in transit, and hosted in the United States. Its privilege guidance centers on United States v. Heppner, the February 2026 Southern District of New York ruling that a defendant's exchanges with a consumer AI tool were not privileged. GC AI points out that the court left room for tools used at counsel's direction under enforceable confidentiality terms. It tells lawyers they can treat GC AI like any trusted cloud tool, such as Google Workspace, Slack or Asana. OpenAI, Anthropic, Google, xAI, Cohere and Reducto process customer content on zero retention terms. Claude Fable 5 is the exception, with Anthropic keeping its data for 30 days, and it stays off until an admin enables it. Users delete inputs and outputs whenever they choose, and an organization's full erasure follows a written request.
Customer content stays the customer's property under section 7.2 of the subscription terms, with a license to LegalOn only to provide the service. Each customer account runs in a segregated environment with strict access controls, and data is encrypted at rest and in transit. Azure OpenAI processes content under terms that it is not used to train, retrain or improve the models and is not stored for any period, including for abuse monitoring. Section 7.3 lets LegalOn aggregate or deidentify customer content into analyses it owns and uses to improve the service, provided they cannot be linked to the customer. Section 2.2 states that LegalOn is not a law firm and that communications between LegalOn and the customer carry no attorney client privilege. Work product handling is not addressed.
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.
The product is sold to lawyers for in house legal work, and GC AI states that it does not give legal advice; it helps attorneys and their companies deliver advice more efficiently. The services agreement makes the customer responsible for having users review output and for meeting their own legal, regulatory, professional licensing and fiduciary duties. Exact Quote is presented as support for the lawyer's duty to verify sources. GC AI also quotes New York Formal Opinion 2024-5, which says a lawyer must review all generative AI output, citations included, before using it for a client or a tribunal. Lawyers are pointed to their local bar for current rules. Stakeholder seats keep non lawyers to factual questions about shared contracts and send judgment questions to the legal team. GC AI states that it assists with legal work in every jurisdiction, and users set the governing law in each request.
Section 2.2 of the subscription terms says LegalOn is neither a law firm nor an attorney and is no substitute for an attorney's advice, and the website terms add that it gives no legal advice. Solution pages sell review to procurement, sales and contract management teams as well as lawyers, and the law firm page offers playbooks that adjust to each client's risk profile. Competence and supervision duties are not addressed, and international playbooks give guidance across 23 countries with no stated limit on where the product may be used.
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.
The In-House Legal Bench, published in May 2026, is how the company evaluates its own output. Six R&D attorneys wrote 100 in house tasks across ten categories, with answer keys averaging 12 criteria each. An LLM judge marks each criterion pass or fail, and attorneys reviewed a sample of its verdicts by hand. Pass rates are published by category, from 81.6% on summarizing documents to 91.4% on comparison and benchmarking, and GC AI says the results drive product changes. Claude Fable 5 led every other model in GC AI's suite on a benchmark of 100 demanding in house tasks, by GC AI's account. Admins on Team and Enterprise plans can switch off Anthropic, OpenAI or xAI models for the whole organization, and a settings table records who changed each provider and when. An AI Governance and Risk Management Policy sits in the trust center beside the security, conduct and acceptable use policies, shared on request. Who inside GC AI answers for model behavior is not stated.
The 2026 Contract Review Benchmark is LegalOn's published test of its own system. Pairwise reviews were judged by an LLM blind to authorship, and legal experts validated a sample of its decisions. Results are reported by provision type, with a report on four failure modes of general models, and a workflow survey of 500 legal professionals sits beside it. Attorneys on staff write the playbooks and keep them current as laws and standards change. An owner for model governance is not named.
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.
Version 4.0 of the data processing agreement, from June 2026, and an information security addendum set the data rules. GC AI processes personal data only on the customer's instructions. After the term ends it deletes all customer data within 30 days of a written request, at downstream vendors too, and clears backups within 90 days. Users can delete inputs and outputs from the app at any time, and data is kept only while the account is active. The subprocessor list names each provider with its purpose, data types and hosting location, and was last updated 18 September 2026. GC AI emails customers before adding or replacing one, allows 30 days to object, and lets the customer terminate if no solution is agreed within 90 days. A confirmed security incident is reported without undue delay, with cause, mitigation and updates as they become available. Sign in runs through WorkOS with SSO over SAML or OIDC, multifactor authentication and organization roles, and custom roles limit what each member can use. Production code is scanned daily for malware, a third party penetration test runs at least once a year, and backups are encrypted and replicated.
Each customer account runs in a segregated environment with strict access controls, data is encrypted at rest and in transit, and LegalOn runs annual penetration tests, regular vulnerability scans and a patch management process. Contracting plans add enterprise single sign on, multifactor authentication and IP allow lists. The data processing addendum keeps a subprocessor list with functions and locations in the trust center, currently Google Cloud Platform, Auth0, Microsoft Azure for the OpenAI service and Datadog. A new subprocessor comes with prior written notice and ten days to object, and a personal data breach is reported to the customer without undue delay. Under section 9.2 of the subscription terms a customer can export content during the term, and LegalOn may delete it 30 days after the term ends. Trust center controls include data retention procedures, deletion of customer data on exit and tested continuity and disaster recovery plans.
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 self serve services agreement, version 10.0 of 24 September 2026, sets the allocation of loss, and customers buying through an order form sign separate terms. Each party's liability is capped at the fees paid or payable for the affected services in the 12 months before the claim, or $100 if that is greater. Indirect and consequential losses are excluded. Gross negligence, willful misconduct and indemnity obligations sit outside the cap. Against third party claims that the service infringes intellectual property, GC AI defends the customer and pays agreed settlements and awarded damages. The indemnity excludes customer data, connected third party apps, modified output, third party web content and misuse. Its remedies run from securing the right to continue, to replacing the technology, to ending access with a refund of prepaid fees. The warranty covers professional, workmanlike service and a platform that materially performs as documented, with correction or a refund as the remedy. The agreement disclaims output, saying AI accuracy can never be guaranteed and that GC AI has no liability for use of or reliance on output. No insurance is stated.
Section 12 of the subscription terms caps each party's liability at the fees paid or payable in the 12 months before the claim. For a customer with no payment obligation, such as a trial, the cap is $1,000. Lost profits, lost data and consequential damages are excluded, and the cap does not limit the customer's own indemnity or payment duties. Against third party claims that use of the service infringes a United States patent, trademark or copyright or misappropriates a trade secret, LegalOn defends or settles and pays damages finally awarded. The indemnity does not reach the customer's negligence, abuse or misapplication of the service. The warranty promises that the service performs materially as documented, and the rest of the service is provided as is. The trust center holds a 2025 cyber insurance policy released on request, and California law governs the terms.
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.
About 20 apps sit behind Agent Connectors, among them Gmail, Outlook, Google Drive, SharePoint, OneDrive, Dropbox, Slack, Microsoft Teams, Notion, Confluence, HubSpot, Asana, Linear, GitHub and Granola. Legal workflow systems include Ironclad, Agiloft and Checkbox, along with ServiceNow, Jira and the USPTO. Each member connects through OAuth, and GC AI acts only with that member's existing access in the source app. For Microsoft 365, GC AI publishes every delegated Graph permission it requests, from Mail.Send to Sites.ReadWrite.All, with the feature each one serves and why it needs that level. Checkbox, ServiceNow, Google Workspace and the USPTO have their own setup guides covering keys, OAuth apps and admin approval. Contract Intelligence syncs vaults from Google Drive, SharePoint, OneDrive, Dropbox or Ironclad, picking up new files every 15 minutes, with import rules and manual resync. The Word add in installs from AppSource or an XML manifest. A REST API, an MCP server for ChatGPT, Claude and Cursor, and the gcai command line tool expose chats, files, projects, playbooks, skills and vaults, with inference capped at 60 requests a minute per organization. A machine client such as Salesforce Agentforce can reach the MCP server with OAuth client credentials. No connector reaches iManage or NetDocuments.
Word is the main working surface, with review, redlining, drafting, questions and one click AI Revise built on Word's tracked changes. Requests arrive from Slack, email and custom forms, with Microsoft Teams marked as coming soon, and SharePoint, Google Drive and Box connect for direct access to files. A public REST API covers three areas. The Contract and Files API moves contract files and data in and out, and the User Management API manages users, groups, workspaces and departments. The Matter API creates matters from a ticketing tool, form or CRM and keeps status, assignees and messages in sync. Access uses OAuth 2.0 client credentials and is scoped to the workspaces a user already holds. iManage and NetDocuments are not named.
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 service runs on Google Cloud, with Vercel hosting the application and Cloudflare routing traffic. Each organization's data is logically separated, with its own access controls and encryption. Under the data processing agreement, customer personal data is hosted in the United States at all times, and GC AI states that all of its servers are in the United States. Every subprocessor, model providers included, lists the United States as its hosting location. Processing may happen elsewhere. The agreement lets GC AI and its subprocessors process personal data wherever they operate when needed to provide the service, with transfers covered by the Data Privacy Framework or standard contractual clauses. The United States is the only hosting location offered, on every plan.
Hosting runs in the United States on Amazon Web Services and Google Cloud Platform, with a segregated environment for each customer account. ISO 27017 certification covers the controls for multi tenant cloud operation. The data processing addendum brings in standard contractual clauses and the UK addendum for personal data moved from Europe, and the privacy policy says personal information may move to the United States or Japan. No single tenant, private or regional option is offered, and where Azure OpenAI processes model calls is not stated.
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 certification, renewed through annual audits, sits alongside a SOC 3 report and a SOC 2 Type I report. GC AI's SafeBase trust center holds the SOC reports, a penetration test summary and policies covering AI governance, acceptable use, anti bribery and conduct. Documents are released through an access request, under a nondisclosure agreement. The information security addendum commits to third party penetration testing of a representative instance at least once a year, vulnerability ranking with CVSS and daily malware scanning of GC AI managed code. Business continuity plans are reviewed each year, and staff with access to customer data are background screened and trained on hire and annually. The reports themselves are released only through that request.
SOC 2 Type II, ISO/IEC 27001:2022 and ISO/IEC 27017:2015 certification are stated. The trust center holds the 2025 SOC 2 report in English and Japanese and the 2025 ISO 27001 and 27017 certificates. A 2025 cloud web penetration test, a network vulnerability assessment and security white paper v1.3 sit beside them, all released through a request for access. Badges on the integration and pricing pages name ISO 27007 and ISO 27011 where the security page names 27017.
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.
Anthropic's Claude family, OpenAI's models, Google's Gemini and xAI's Grok handle chat and analysis. Cohere's embedding model powers retrieval over files, and Reducto parses documents. Requests go to the model best suited to each task and fall back across providers during an outage, and users do not choose a model. Each provider appears on the subprocessor list with zero retention and United States hosting. Claude Fable 5 is the exception, since Anthropic keeps its data for 30 days for safety work, and it stays off until an admin accepts those terms. Admins on Team and Enterprise plans can switch off Anthropic, OpenAI or xAI, with each change logged by person and time, while Gemini cannot be switched off. Before adding or replacing a subprocessor, GC AI emails customers and gives them 30 days to object.
Microsoft's Azure OpenAI service is the named model provider for review and drafting, under terms that it does not train on or store customer data, including for abuse monitoring and debugging. Translation runs on DeepL alongside LegalOn's own translation agent. The subprocessor list places Microsoft Azure beside Google Cloud Platform, Auth0 and Datadog, and a new subprocessor comes with prior written notice. Review runs focused checks per guideline in parallel. Which models serve those checks, and where they run, is not stated.
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.
An individual seat costs $500 a month, billed monthly or yearly by card, and can be bought without a sales call after a 14 day free trial. GC AI says individual pricing is standard and not negotiable. The seat includes unlimited chats and skills, the Word add in, Easy Prompt, analytics on usage and time saved, AI Academy and CLE courses, and the Slack community. Team plans are annual and priced on request, with enterprise SSO, a team skill library, Contract Intelligence, shared chats, solutions attorney support and one legal database. Enterprise pricing is custom. On individual seats, the case law and international law databases are add ons at an unpublished price, each with a one time 30 day trial. API and other usage based features draw on prepaid credits, priced in the platform at purchase and pooled across the organization. Credits expire at the end of the term, usage stops when they run out, and nothing is billed in arrears. Fees are non refundable and renew at the current published price.
Pricing is set in a sales conversation, and the pricing page lays out three plans without figures. Core Review, for solo attorneys and fractional general counsel, includes unlimited chat, review and redlining, 135 or more playbooks, a document repository, more than 100 templates and the Word add in. Contracting Suite adds custom playbooks, the Playbook Agent, Vault and Vault Projects, team training, dedicated support and enterprise sign on. Productivity Suite adds Matter Management with intake and triage agents, a matter dashboard and matter intelligence. Every plan includes unlimited usage and guided onboarding. Entity Management, Board, Translate, international playbooks and managed playbooks are further modules.
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.
In house legal departments are the only market, from solo and fractional general counsel on the individual plan to enterprise legal teams. Customers range from startups to Fortune 500 companies across technology, finance, retail and apparel, manufacturing and healthcare, including Hitachi, Vercel, Snyk, Tipalti, Gusto, Arc'teryx, Columbia Sportswear and Wayfair. The named work runs from commercial contracts, NDAs, DPAs and MSAs to privacy, employment, corporate governance, board materials, regulatory research and portfolio contract review. Ready made playbooks cover NDAs, DPAs and MSAs for SaaS and for commercial use. A playbook run can take the deal stage into account when it suggests fallback language, and it works on drafts that carry tracked changes from earlier rounds. Generalist in house lawyers are the best fit, GC AI says, and it will recommend other platforms to specialized practices. Some teams, it notes, keep a traditional research seat for exhaustive litigation research. The legal databases cover United States federal, state and specialized courts and more than 30 jurisdictions in Europe, Asia Pacific and Latin America.
Buyer pages cover in house legal, legal operations, procurement, contract management, sales and law firms, and industry pages cover construction, financial services, business services, private markets, healthcare, manufacturing and software. Playbooks are specific to contract type and to whether the customer sends or receives the paper, and international playbooks cover common commercial contracts in 23 countries, from the United Kingdom to Singapore. Translation runs across 28 or more languages. The product covers contracting work from intake to signed agreements, plus entity and board records. Litigation and legal research are outside it.
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?
Section 4.9 of the services agreement says GC AI will not use customer data to train generative AI models, including large language models. GC AI adds that its model providers do not train on that data either, and that data from connected apps is used only to answer the user's requests.
Three carve outs apply. GC AI may use deidentified, aggregated content to improve the service and to build insights on market terms, contract positions and industry benchmarks, and once deidentified it is no longer treated as customer data. Material submitted to a preview feature may be used to develop the service, and feedback given through thumbs up or down belongs to GC AI.
Section 7.3 of LegalOn's subscription terms, last modified 1 June 2026, allows LegalOn and its affiliates to aggregate or deidentify customer content, alone or combined with data from other sources. The resulting analyses may be used for internal business purposes "including to improve the Services", and LegalOn owns them and may disclose them as long as they cannot reasonably be linked to the customer. The data processing addendum keeps the same right to use deidentified or aggregated customer data to improve LegalOn's systems after the contract ends.
No clause carves model training out of that use. At the model layer, Microsoft's Azure OpenAI service runs under protections that keep customer data out of training, retraining or improving its models.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
Users delete their own inputs and outputs from the app at any time, and an organization can have all of its data erased by written request. GC AI keeps customer data only while the account is active and describes its retention policies as customer managed. After the term ends it deletes everything within 30 days of a request, including at downstream vendors, and clears backups within 90 days.
Model providers process prompts on zero retention terms and keep nothing after a response. Claude Fable 5 is the exception, with Anthropic keeping its data for 30 days once an admin enables it. Citation snippets and case metadata stay in chat history for display.
Model calls through Azure OpenAI leave no customer data stored for any period, including for abuse monitoring and debugging. Contracts in Vault stay for the subscription term, a customer can export them, and LegalOn may delete them 30 days after the term ends. Personal data is kept as long as reasonably necessary, and no customer setting for retention during the term is described.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
Permissions in GC AI follow its own model. New chats, skills and company profiles are private to their creator until shared, and a project is either private to invited members or open to the whole organization, with View, Edit and Owner levels. Contract Intelligence vaults start access controlled, and linking a vault to a project gives nobody new access.
Custom roles, access tiers and user groups set what each member can use, and Stakeholder seats confine outside counsel to the vaults they are added to. Under the services agreement, organization admins may access any member's data. Agent Connectors act with each member's own access in the source app, so retrieval from Gmail, SharePoint or Drive follows that app's permissions, while content copied into GC AI follows GC AI's model.
Inside a customer, contracts are organized by workspace, project or department, and workspace access is set by user group, with changes cascading to every user in the group. API calls are scoped to the workspaces a user already holds. Each customer account runs in its own segregated environment. Walls at the level of a single matter are not described.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
Section 5.2 of the data processing agreement commits GC AI to tell the customer promptly of any valid subpoena, warrant or court order compelling disclosure of customer personal data, unless the law forbids it. The notice gives the customer time to seek a protective order. Where notice is barred and GC AI judges a demand unlawful, it will take reasonable steps to challenge it. Other inquiries, from regulators or individuals, are redirected to the customer.
The services agreement adds a mutual confidentiality term covering all customer data. A party compelled by a court or regulator gives notice before disclosing where time allows, helps seek protection and shares only what is legally required. No transparency report is published.
Section 8.2 of the subscription terms requires prior notice of a legally compelled disclosure where the law permits, and reasonable help if the customer contests it. Under the data processing addendum, LegalOn tells the customer of requests from regulators about personal data and does not answer them without approval. The privacy policy allows disclosure to law enforcement and authorities for legal compliance. No transparency report is offered.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
Midpage AI supplies the case law, drawing opinions from court websites and government records and updating daily. GC AI holds no case law collection of its own and fetches opinions live from Midpage's API. The International Law database takes case law and legislation from court websites, government legal portals and official gazettes through Moonlit, refreshed daily, and links each authority to its official portal.
United States coverage runs to federal courts at every level and to state supreme and appellate courts in all 50 states and DC. Some state trial courts are included, along with tribunals such as the Tax Court, PTAB, TTAB and NLRB. Abroad it reaches more than 30 jurisdictions, some with case law only or legislation only, and a coverage view inside the app lists current sources. The rights basis for the material is not stated.
Playbooks are written and maintained by LegalOn's attorneys for each contract type and negotiating position, more than 135 of them, and are kept current as laws and standards change. More than 100 attorney drafted templates sit beside them. The legal sources behind each standard are not named.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
Treatment flags appear beside cited cases where later history exists. Negative marks a case reversed or overruled, cautionary one that was distinguished, questioned or criticized, positive one followed or affirmed, and neutral history with no clear direction. GC AI reads the full opinions and checks treatment status as it answers.
Recent decisions and cases with little later history may carry no flag, and users are told to verify critical citations themselves. Midpage AI supplies the case law, and where the treatment data comes from is not said. International authorities show how often later decisions cite them, and some statutes show whether a provision is in force.
Review tests contracts against playbook standards rather than case law, and the playbooks are kept current as laws change. No flag on cited cases or check of later history is part of the product.
Refusal and Uncertainty Behavior
What does the product do when the answer is not in the corpus?
Exact Quote ties statements to highlighted source text, the Research Agent runs further rounds of research until it has a thorough answer, and complex tasks end with a completeness check before findings are reconciled. On statutes, in force badges come with a note that a missing badge says nothing about current status.
Stakeholder vault chat answers factual questions about shared contracts and sends questions of legal or commercial judgment back to the legal team. No behavior is described for a question the sources cannot answer.
Review flags each issue with an importance of low, medium or high and supplies the playbook guidance and sample clauses behind it. No path is described for an issue the product cannot assess.
Fabricated Citation Record
Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?
The AI Hallucination Cases database maintained by Damien Charlotin, which records court decisions worldwide that address hallucinated AI content and the tool involved where known, has no entry naming GC AI. GC AI is sold to in house teams for contracts, research and advice to the business rather than court filings, and its blog keeps a tracker of AI hallucination sanctions decisions.
The AI Hallucination Cases database maintained by Damien Charlotin, which records court decisions worldwide that address hallucinated AI content and the tool involved where known, has no entry naming LegalOn. Its products review, draft and manage contracts for in house and contracting teams.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
The security FAQ names ABA Formal Opinion 512 and New York Formal Opinion 2024-5. It quotes the New York opinion on reviewing all generative AI output before relying on it, and tells lawyers to check their local bar for current rules. It also points to the Northern District of Texas rules on disclosing AI use to a court.
The July 2026 sanctions tracker on GC AI's blog restates Opinion 512's point that the duty to verify stays with the lawyer, and its privilege guidance rests on United States v. Heppner. No document maps product features to the duties in each opinion.
The company's research covers AI adoption, a workflow survey of 500 legal professionals and its contract review benchmark. No public material engages ABA Formal Opinion 512, a state bar opinion or Japanese bar guidance.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
GC AI is sold to in house legal teams. Its customers page quotes legal leaders at Vercel, Arc'teryx and Interface, and its workflows, output style and pricing are built for corporate counsel. Savings land in the company's own legal budget. GC AI says customers often cut outside counsel spend by 30%, offers an ROI calculator, and gives admins analytics on usage and time saved. Its December 2025 ROI study of more than 100 customers reports 14 hours saved per lawyer each week. Viant's chief legal officer describes working an issue through GC AI before paying outside counsel by the hour.
LegalOn sells to in house legal, legal operations, procurement, contract management and sales teams, and to law firms. Its law firm page pitches taking on more clients by cutting manual review time by up to 85%. TriHealth, a Cincinnati health system, reports clinical trial agreements that once took hours now reviewed in about 20 minutes, a 75% reduction. No per matter record of AI assisted work for fee purposes and no guidance on billing, fee or client disclosure treatment is published.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
A public subprocessor list gives each provider's purpose, data types, hosting location and retention status, beside GC AI's data processing agreement, information security addendum, services agreement and privacy policy. A models page names Anthropic, OpenAI, Google, xAI and Cohere and explains how each handles data, and the security FAQ answers common procurement questions.
The trust center adds SOC reports, a penetration test summary and policies through an access request. GC AI completes custom security questionnaires at its discretion and may charge for extensive ones. No disclosure statement is published for a legal team to give the business units it serves.
The trust center keeps the subprocessor list that the data processing addendum points to, with Google Cloud Platform, Auth0, Microsoft Azure for the OpenAI service and Datadog. A new subprocessor is announced with ten days to object. The SOC 2 report, ISO certificates and security white paper are released on request, and no client facing disclosure template is offered.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
Chats export as PDF, DOCX or Markdown, whole or one message at a time, with an optional citations section listing each citation's number, quoted text and source file. Tables export to CSV or XLSX, and an API chat can be saved into history with a shareable link. Admins see organization usage analytics and a log of model provider changes.
For court rules on AI disclosure, GC AI points lawyers to examples such as the Northern District of Texas and to their local bar. The export names no model.
Review ties each issue to the playbook standard behind it, and Matter Management keeps each request's history, status and cycle time. No record of AI use for a court filing is offered.
Which one fits
Choose GC AI if
- Your playbook is your own. GC AI builds review checks from your templates and negotiated deals, and Smart Checks catch clauses your playbook misses.
- You also answer legal questions for the business. GC AI researches United States case law with treatment flags, or case law and legislation from more than 30 other jurisdictions, in the same chat.
- Seeing the cost up front matters. GC AI publishes its individual seat price and sells it by card after a 14 day free trial.
Choose LegalOn if
- You want review standards ready on day one. LegalOn ships more than 135 playbooks written and maintained by its own attorneys.
- Standard paper should move without a lawyer. LegalOn's Triage Agent approves standard agreements and flags nonstandard terms, and its Intake Agent fills in missing details from requesters.
- You work across languages. LegalOn translates contracts across 28 or more languages and retranslates changes back into the original.
In summary
GC AI
In house legal departments are GC AI's only market, and its contract review runs on the team's own positions. Easy Playbooks turns a team's templates and past deals into checks, and Smart Checks flag clauses the playbook does not cover. According to the AI Legal Index, GC AI also answers research questions from United States and international legal databases and acts in business apps through Agent Connectors.
LegalOn
LegalOn is a contract review and legal workflow platform for in house legal and contracting teams, from LegalOn Technologies, which began in Japan. Plans run from Core Review, with more than 135 attorney written playbooks and a Word add in, to suites that add custom playbooks, a contract Vault, matter management and intake and triage agents. According to the AI Legal Index, LegalOn publishes an annual contract review benchmark of its system against foundation models, and hosts on AWS and Google Cloud in the United States.
Questions buyers ask
GC AI vs LegalOn: what is the main difference?
LegalOn centers on contract review against playbooks its attorneys write and maintain, with matter management, a vault and translation around it. GC AI builds review from the team's own positions and adds research, advice in chat and actions in business apps. From the AI Legal Index, based on each vendor's own published materials as of October 12, 2026. No vendor pays for placement.
Which one publishes a price?
GC AI's individual seat is listed at $500 a month. LegalOn lists what each plan includes without a figure, and buying starts with a demo. From the AI Legal Index, based on each vendor's own published materials as of October 12, 2026. No vendor pays for placement.
What did LegalOn's and GC AI's own benchmarks measure?
Both publish benchmarks they ran themselves. LegalOn's 2026 Contract Review Benchmark set its system against 11 named models across 3,282 pairwise reviews on 21 guidelines. GC AI's own benchmark measured answers on 100 in house tasks against more than 1,200 attorney written criteria. From the AI Legal Index, based on each vendor's own published materials as of October 12, 2026. No vendor pays for placement.
Which models sit underneath?
GC AI names Anthropic, OpenAI, Google and xAI as model providers on its subprocessor list. LegalOn names Microsoft's Azure OpenAI service as a provider, with no training on or storage of customer data there. From the AI Legal Index, based on each vendor's own published materials as of October 12, 2026. No vendor pays for placement.
Does either handle legal intake?
LegalOn's Productivity Suite adds matter management, an Intake Agent that completes and screens requests from email, Slack or a form, and a Matter Dashboard of cycle times and workload. GC AI works with intake tools such as Checkbox and ServiceNow through Agent Connectors, and Stakeholder seats give business partners limited access to shared contracts. From the AI Legal Index, based on each vendor's own published materials as of October 12, 2026. No vendor pays for placement.
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.
The two products sit in different classes. LegalOn is a contract review and legal workflow platform built on attorney written playbooks, and GC AI works as a general legal assistant for in house departments. They overlap on contract review, and this page answers a comparison buyers already make. LegalOn Technologies began in Japan in 2017 and runs a United States and global business beside its Japanese one, and no parent company is stated. GC AI's maker, General Counsel AI, Inc., is a San Francisco company with no parent. Neither vendor reviewed this page.