LegalOn is a contract review and legal workflow platform for in house legal teams, legal operations, procurement, contract management and sales, with a law firm edition. Review runs a contract against attorney written playbooks, ranks each issue low, medium or high and writes redlines in Word or the browser. More than 135 prebuilt playbooks cover common agreements by contract type and negotiating position, and the Playbook Agent turns a team's templates, guidelines or past redlines into playbooks of its own.
Assistant answers questions about contracts. Matter Management takes requests from email, forms and Slack through intake and triage agents, Vault stores signed agreements and extracts terms, obligations and renewals, and Translate works across 28 or more languages. Entity and board management sit on the same platform. Plans run from Core Review for a solo attorney to a Productivity Suite for a whole department. Two corporate lawyers founded the company in Japan, and it now has headquarters in Tokyo and San Francisco, more than $200 million in funding and more than 9,000 customers.
Side by side on the same 15 capability axes and 12 legal signals: where the two part company, and what neither one publishes.
Vendors in the same categories as LegalOn whose graded profiles look most alike, with a line on what each product does.
Similar is not the same, so check that each one does the job you need. No vendor pays for placement.
Ordered by how closely the graded profiles match across the 15 capability axes, inside the same categories. See how each axis is graded in the methodology.
All 15 axes, graded from public sources on the date shown. Hover a grade to see what the letter means on that axis.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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 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.
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.
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.
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.
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.
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.
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.
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.
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.
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, 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.
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.
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.
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.
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.
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.
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 public pages on file for LegalOn, with the recorded signals each one supports and the date it was last read. Open any of them and check the reading against the record.
Prompt and Output Retention, Ethical Walls and Matter Segregation
Read Oct 12, 2026
Outside Counsel Guideline Readiness
Read Oct 12, 2026
Fabricated Citation Record
Read Oct 12, 2026
Primary Law Corpus Provenance
Read Oct 12, 2026
Refusal and Uncertainty Behavior
Read Oct 12, 2026
Billing and Fee Posture
Read Oct 12, 2026
Third Party Request and Subpoena Notice
Read Oct 12, 2026
Client Data in Training
Read Oct 13, 2026
LegalOn published a set of workflow additions: Cross Document Review for analyzing a whole contract family together, searchable negotiation history through the LegalOn Assistant, and an upgrade to AI Revise that drafts and inserts language for missing provisions inside the Word add in. Teams can also set a department level editor name for redlines in Word for the Web.
A signal records what public sources say on the date shown. It is not a grade and it is not a recommendation. Where a signal reads Not addressed, it means the index did not locate the material in public sources on that date, which is a statement about disclosure rather than about the product.
Can material a lawyer puts into this product be used to train a model?
The published agreement expressly reserves a right to train on customer content, with no opt out located. Any de identification, anonymization or aggregation qualifier is recorded in the summary.
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.
How long does the product keep what a lawyer typed, and can that be set to zero?
Retention is acknowledged in public materials with no stated period.
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.
Does retrieval respect the firm’s ethical walls, or can the model read across them?
The product maintains its own permission model, documented, requiring the firm to keep it aligned.
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.
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
Terms commit to notice where lawfully permitted. No transparency report located.
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.
Where does the law in this product come from, and does the vendor have the right to use it?
Sources are identified without stating the license or rights basis.
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.
Does the product tell you when the authority it just cited has been overruled?
No located public material addresses whether authority is checked for subsequent history.
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.
What does the product do when the answer is not in the corpus?
The product exposes a confidence or grounding score without an explicit abstention path.
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.
Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?
No court order, opinion or disciplinary record addressing fabricated or hallucinated legal citations produced by this product has been located as of the date shown. This is a statement about the public record on that one subject, not a finding about the product, and this signal is not a litigation history.
The AI Hallucination Cases database maintained by Damien Charlotin, 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.
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
No located public material engages with bar or ethics guidance.
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.
Does the vendor address what happens to the bill when the work takes an hour instead of six?
Public materials claim time savings without addressing billing or disclosure, and the product sits inside a fee relationship between a lawyer and a client where those savings would change the bill.
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.
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
A current subprocessor or model provider list is published.
The 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.
If a judge’s standing order requires an AI disclosure, can the product produce one?
No located public material addresses court disclosure or verification certification.
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.
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.