Ontra vs ProVision: how they compare in 2026
Ontra and ProVision both manage side letters and most favored nation elections for private funds. Ontra does it inside a wider private markets platform, while ProVision is a dedicated tool built by former fund formation lawyers. Ontra sits in the top two bands on twelve of fifteen axes and ProVision on seven of fifteen, identical on seven. Ontra's lead is published governance. It holds ISO 42001 for AI management alongside SOC 2 Type 2 across all five criteria, has subject matter experts review AI output for errors, and publishes a subprocessor list with change alerts. Its public terms cap liability at $100, though a signed customer agreement, which is not published, replaces them. ProVision's counterweight is isolation and its customer base. Each customer gets a dedicated single tenant instance on AWS, and it names Cleary Gottlieb, Fried Frank, Goodwin and Ropes & Gray among firms using it, with over 5,000 side letters processed in 2025. Its agreement, data processing terms and SOC 2 report are available only by email.
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.
The models are the engine of the data products and a layer on the service products. Insight abstracts clauses and covenants from fund and credit agreements into structured obligation data, Accord produces AI markup against a digital playbook, and DDQ generates responses from a precedent library — all model-driven. But Contract Automation, the flagship, states on the pricing page that the contract resource is a human: qualified contract professionals on Standard, qualified lawyers on Advanced, lawyers with top-tier firm experience on Premier. Remove the models and an outsourced negotiation service and an entity directory remain saleable. That places this at B rather than A: a core capability is genuinely model-driven, sitting on a workflow and document platform that would still function without it. Pages read 1 September 2026.
The models drive a core capability and the vendor states plainly that the product does not depend on them. Extraction is the model's job: uploaded side letters, LPAs and master documents are read and their provisions and investor-specific terms structured automatically. But the support FAQ says in terms that the platform does not require AI to run and that the most advanced AI solutions are deployed only where they add value, with guardrails to retain control over outputs, and a customer's own published account describes AI-powered functionality as something added when appropriate according to each client's preferences and data security policies. So the AI is optional by design and per-client. What remains without it is real rather than residual: a structured repository of side letters and LP comment memos, MFN election form generation and response tracking, provision comparison and merging, versioning and an action record. That is a workflow and document system the models sit on top of, which is this band rather than the one above. Checked 4 September 2026.
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.
Accuracy is asserted and never measured. The AI page promises “reliable AI” and “expert-validated, actionable intelligence”, and the platform markets AI Search that answers questions “informed by the full scope of your agreements”, but no accuracy figure, no test set, no evaluation and no named failure mode was located on any page read on 1 September 2026. Nothing published establishes that an answer links back to an openable source passage a reader can verify, which is what the B band requires alongside a described retrieval method. The subject-matter-expert review process that catches hallucinations is real and is graded on Autonomy and Oversight, where it answers the question the band actually asks; it is not spent again here. Two limbs of the higher bands do not apply, since the corpus is the customer’s own fund documents rather than primary law, so grounding to primary authority and citation-status checking are outside what this product claims.
Accuracy is asserted, real architectural controls exist, and nothing is measured. Two design commitments are published and both bear on grounding: extraction is stated to structure provisions while preserving the original legal text, and comparison is described as operating without breaking traceability, so an output can be traced to the source clause it came from. The support FAQ adds that fail-safes or guardrails are provided to prevent hallucinations. Against that, no accuracy figure, no test set, no evaluation, no error rate and no description of extraction method appears on any surface, and nothing states what proportion of provisions are extracted correctly or how a mis-extraction surfaces to a reviewer. The bottom band does not fire here, because this is not a bare hallucination claim standing alone: preservation of original text and traceability are genuine controls. A Data Security White Paper described as a technical deep dive into the architecture exists but is obtainable only by emailing the company. Searched the home page, the ProVision overview, the about page, the support FAQ and the trust centre on 4 September 2026.
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.
A written human-review commitment with a described mechanism. The security page publishes a Human-in-the-Loop Model under which subject-matter experts continuously review text outputs for accuracy, flag potential hallucinations and enforce consistency across repeated questions, then troubleshoot root causes and attribute them to retrieval-augmented generation prompting, query understanding or embedding models. That last detail is unusual: it names the layers of its own pipeline where failures are diagnosed. The pricing page adds a second published control by tiering who performs the work, from contract professionals to lawyers with top-tier firm experience. What is missing for A is the rest of the control structure — no thresholds, no statement of what runs unattended versus what a customer must approve, and no described in-product review surface or escalation route. B on the strength of the review commitment, held there by the absent thresholds.
A clear written commitment that the lawyer stays in control, with real review surfaces and no described control structure. The about page states that the technology is there to assist rather than to second-guess professional judgement and that ProVision keeps the lawyer in control, and the overview repeats that structuring happens without compromising legal judgement. The review surface is concrete rather than asserted: extracted provisions and investor information are presented for review, MFN elections are defined by rules and parameters the team sets, and the home page describes clear visibility and control at every step with a record of every action, approval and document version. What is absent is the structure around it. No threshold is published at which the system acts without a reviewer, nothing describes what happens to extractions nobody approves, no confidence signal is surfaced against an individual provision, and the guardrails referred to in the support FAQ are named without being 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.
Attribution is strong and the figures sit on the wrong side of it. Named customers carry named officers with titles: Vincent Taurassi, General Counsel and COO at Sentinel Capital Partners; Lizette Perez-Deisboeck, General Counsel and CCO at Battery Ventures; Jonathan Romick, General Counsel at Linden Capital Partners, describing an SEC production; Ed Zelaski, Director of Compliance at Blue Point. Blackstone and Bain Capital Credit carry their own case studies. Separately the vendor publishes portfolio figures — 1,000-plus customers, 2 million-plus documents processed, 9 of the top 10 PEI-ranked firms, and 96% customer retention with a genuine methodology footnote stating it is the average across customers using a platform solution for at least a year as of December 2025. That footnote is the kind of dated, assessable method the A band asks for, but it describes the vendor’s book rather than what changed at a named firm. B: named customers without figures, and figures without the named customer.
Named customers at the top of the market and figures that do not attach to any of them. The customer list is specific and published by the company: Cleary Gottlieb, Fried Frank, Goodwin, Paul Weiss, Proskauer, Ropes & Gray and Willkie Farr & Gallagher, described as more than ten of the world's largest law firms. Two named individuals are quoted with their roles, Theresa Spartichino, Director of Practice Technology at Ropes & Gray, and Conan Hines, Director of Practice Innovation at Fried Frank, and Fried Frank has separately published its own announcement about deploying the platform, quoting Becky Zelenka, partner and co-head of its Private Equity Funds group. The volume figures are dated and substantial: in 2025 the platform is stated to have processed more than 5,000 side letters across over 450 matters, supporting more than 150 billion dollars of capital raised across six named markets. What holds this at B is that the two sets do not meet. No figure is attributed to any named firm, the quotes describe operational clarity and rapid adoption without measurement, and no case study is published.
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.
Substantive commitments on the two questions that decide most of this axis, and silence on the third. The security page states plainly that Ontra never uses customer data to train models, and that data passed to third-party LLM providers is processed only to deliver the service and deleted afterwards — a position on what the model provider retains, which most vendors in this pull do not give. Terms of Service clause 10.2 commits Ontra to a reasonable degree of care over User Data. Against that, clause 6.2 reserves the right to collect usage data on an aggregated and anonymised basis to improve products, except as limited by a Customer Agreement, so the no-training promise lives on a marketing page while the published agreement reserves an improvement use. Segregation is the gap: nothing documents tenant separation, and clause 10.2 warns that other Users with access rights may reach User Data. Privilege and work product are not addressed. B, held off A by segregation and by the Customer Agreement being unpublished.
The segregation limb is answered better than almost anything in this corpus and the rest of the picture is gated or unread. What is published is specific and checkable: ProVision is deployed in a single-tenant AWS environment logically segregated per customer, documents and extracted data sit in a dedicated instance and are stated never to be commingled with other clients' data, there is no shared document storage across customers, access runs on granular role-based control, and encryption is AES-256 at rest with TLS 1.2 or higher in transit. That is tenant-level separation documented at the level a law firm buyer requires. Three things hold it here. No privilege or work product treatment is named anywhere, which the top band requires as its own limb. The training question is addressed by a published FAQ entry, Do you use our data to train AI models, whose answer sits in a collapsed accordion this instrument could not expand, so the position could not be established. And a further claim needs recording rather than crediting: the trust centre describes a zero-knowledge framework under which ILS cannot access customer provisions or investor data, and end-to-end encryption at every stage, which sits in tension with a product that extracts and structures provisions server-side. Nothing published reconciles the two, and the white paper that would is available only by email.
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.
A real, product-scoped position rather than a website disclaimer. Terms of Service clause 12.2 is headed NO LEGAL OR OTHER ADVICE and states that nothing in the Services, the software or the documentation constitutes legal advice, that Ontra is not a law firm and does not provide legal services, advice or representation, and that no attorney-client relationship is formed. It also places responsibility for decisions taken in reliance on output with the user. That clause reaches the Platform, not just the marketing site, which is what separates this from most of the lane. It is worth reading against the business: Ontra operates the Ontra Legal Network and the pricing page sells access to qualified lawyers who negotiate the customer’s contracts, so the no-legal-services clause and the commercial offer sit in visible tension. B rather than A because nothing addresses the buyer’s own competence and supervision duties and no jurisdiction limits are named; ABA Formal Opinion 512 is not mentioned.
Something real is published about professional judgement and nothing at all about the advice line. The about page states that the technology assists rather than second-guesses professional judgement and that ProVision keeps the lawyer in control, and the overview describes structuring side letters and LPAs without compromising legal judgement. The audience is unambiguous and narrow, being private investment funds lawyers at law firms and fund formation teams, so there is no consumer-facing surface and the disclosure limb of the top band does not bite. What is missing is the advice line itself: no statement that outputs are not legal advice, no requirement that a lawyer verify an extracted provision before relying on it, no rule of professional conduct, bar or regulator named, and no jurisdiction limit stated despite the company reporting work across six markets with different regimes. The document that would ordinarily carry a disclaimer is the Terms of Service, described on the trust centre as the governing agreement for using ILS platforms and obtainable only by emailing the company, so it could not be read. Neither this band nor the one below reads cleanly, since there is no boilerplate disclaimer to point at and the audience is not ambiguous; graded at the nearer and the reason stated.
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.
Ontra holds ISO 42001, the international management-system standard for AI, stated on the security page and carried as a badge on the home page. A certified AI management system is a published governance framework with real substance rather than a set of principles, and it is the second instance of this certification in the pull after Corlytics. What is absent is everything the A band adds: no individual or committee inside Ontra is named as accountable, no pre-release testing regime is described, and no result is disclosed about uneven output across document types, jurisdictions or counterparties. Security certifications are excluded from this axis by the band and the SOC 2 and ISO 27001 attestations are graded on Security Certifications instead, so ISO 42001 is the only certification spent here. B. Checked 1 September 2026.
No governance position was located. There is no responsible AI page, no principles statement, no named owner accountable for model behaviour, no evaluation or testing regime, and nothing at all on bias or on uneven extraction quality across document types, drafting styles or jurisdictions. The site inventory was taken from the navigation and footer across three pages on 4 September 2026 and runs to ProVision Overview, Trust Centre, Blog, Support, About ILS, Our Team, Careers, Press Announcements, Contact, Privacy Policy and Cookies Policy; none of them is a governance surface. The trust centre's Resource Vault lists eight items and every one is a security, privacy or contractual document rather than an AI governance artifact. The nearest published language is the support FAQ's reference to fail-safes and guardrails, which is a product assurance rather than a governance framework and is graded on the accuracy and autonomy rows instead of counted twice here. A description of the company as taking a lawyer-led and disciplined approach to AI comes from its lead investor rather than from the company.
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.
Most of the ground is covered and the gap is incident practice. The security page publishes AES-256 with rotating keys at rest and TLS 1.2 or above in transit, states that third-party LLM providers encrypt in both states, and commits to deleting data passed to those providers once processing is complete. It names a dedicated security team and the tooling classes it runs, listing SAST, DAST, CDR, EDR, continuous GRC, WAF and MDM. A subprocessor list is published on the trust centre at trust.ontra.ai, which also offers email notification of subprocessor changes — a live disclosure mechanism rather than a static page. Not located: any incident response or breach notification practice, and any statement of how long documents and generated outputs are retained inside the platform itself, as distinct from the zero-retention commitment at the model layer. B on the band’s own named exception for an unstated incident practice.
Access control and encryption are published in detail and everything governing the data afterwards sits behind an email request. Published in the clear: AES-256 at rest, TLS 1.2 or higher in transit, single-tenant AWS deployment with logical segregation per customer, granular role-based access control, real-time monitoring, redundant backups and configurable data residency options. That is a real account of how the data is held. What is not published is the rest of the set. No retention period appears anywhere, no deletion route or certification is described, and no subprocessor is named on any readable surface. The documents that would answer each of those are listed on the trust centre and every one resolves to a mailto link at the company's information security address: a GDPR Overview stated to cover where data is hosted and which subprocessors are involved, a Data Processing Agreement, an Incident Response Overview and a Privacy Policy. Where a portal does not state whether its access flow fulfils without a sales conversation, the lower tier is assumed and that is the position here. A Privacy Policy also sits at a public footer URL and was not opened in this pass.
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 published allocation is specific and it runs one way. Terms of Service clause 13.2 caps Ontra’s aggregate liability at $100, disclaims all consequential, incidental and special damages including loss or corruption of data, and carves out only fraud and willful misconduct. Clause 12.1 provides the Services as-is with all warranties disclaimed, and clause 13.1 runs the only indemnity from the user to Ontra. There is no warranty on output, no insurance position, and no indemnity flowing to the customer. The instrument that would actually govern a buyer is not published: clause 1 states that where a user has access under a customer’s written Customer Agreement, that agreement supersedes these Terms, and no Customer Agreement, MSA or DPA was located on the site on 1 September 2026. C rather than D because a buyer can read a specific figure and carve-out before signing; C rather than B because what is published disclaims the exposure the product creates rather than standing behind it.
Nothing on the allocation of loss could be read, and the governing document is named rather than published. The trust centre lists a Terms of Service and describes it as the governing agreement for using ILS platforms, ensuring legal clarity and compliance, and its View link resolves to a mailto address at the company's information security team. The Data Processing Agreement sits behind the same gate. No indemnity, no cap, no carve-out, no warranty on output and no insurance position appears on any readable surface, and neither the home page, the overview, the about page, the support FAQ nor the trust centre body carries any liability language at all. This is a documented absence rather than an established silence: the vendor plainly has an agreement and states so, and it is not published in a form a buyer can read before entering a sales conversation. The grade records what a reader can establish from published material as located on 4 September 2026, and obtaining the Terms of Service would be applied as an amendment with its own date. It is the cheapest available upgrade on this record.
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.
Real named integrations, documented at the level of what they do rather than how to configure them. The Ontra MCP Server gives a customer’s own LLM real-time, read-only access to Atlas entity data, letting a firm query entities and ownership structures from its existing AI tool — direction and permission model both stated. Ontra for Word is named in the Terms of Service as an application plug-in, putting the product in the drafting surface lawyers already use. The Atlas pricing panel includes a Standard API package, the DDQ panel lists flexible exports, and Insight publishes side-letter compliance exports. Contract Automation includes a document management system in all three editions. B rather than A because no integrations page, developer index or configuration documentation was located on 1 September 2026, and no connector to a legal document management system such as iManage or NetDocuments is named.
No integration into the systems legal work already lives in was located, and the product's own described workflow is upload and export. Documents enter by being uploaded, described as side letters, LPAs and related documents uploaded in minutes, and outputs leave as generated election forms in PDF and Word. Nothing connects to a document management system, and neither iManage nor NetDocuments nor SharePoint is named anywhere; no practice management, matter management, e-billing or fund administration system is named either; and there is no integrations page in the site navigation or footer, no API reference and no developer documentation. The one connection published is authentication rather than practice systems: the support FAQ confirms single sign-on with multi-factor authentication, or username and password with two-factor, or both. That governs how a user reaches the platform, not how a matter file reaches it. The absence carries weight on a product whose input is execution-version documents that in an AmLaw firm already sit in a document management system. Searched the home page, the ProVision overview, the about page, the support FAQ and the trust centre on 4 September 2026.
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.
Cloud delivery is obvious and neither dimension is stated. The product is a web platform signed into at app.ontra.ai, but no page read on 1 September 2026 — home, AI capabilities, security and privacy, pricing, or the Terms of Service — states a tenancy model or offers a data residency region, and no processing location is given as distinct from storage. The one thing published that touches location is that third-party LLM providers encrypt data in transit and at rest, which says nothing about where either sits. The trust centre at trust.ontra.ai is a Vanta portal whose body did not render to automated retrieval and may well carry hosting and region detail; that is a limit on this reading rather than a gap in the vendor’s disclosure, so nothing is graded against Ontra for it. C on the band’s own words, which are true here: cloud delivery is implied and neither the tenancy model nor the region is stated on any readable surface.
The tenancy model is stated clearly and unusually prominently, and the residency half is offered without detail. ProVision is published as deployed within a secure single-tenant AWS environment, logically segregated per customer, with each customer's documents and extracted data in a dedicated instance and no shared document storage across customers. The vendor makes the point comparatively, stating that most legal technology providers operate shared multi-tenant environments and that ProVision is different, so this is a positioning claim it has committed to rather than a passing mention. Amazon Web Services is named as the host. Residency is where it stops short: configurable data residency options are listed as a feature and no region is named anywhere, so a buyer knows a choice exists without knowing what the choices are. Nothing states where processing happens as distinct from where data is stored, which matters on a product whose extraction step may run elsewhere, and no model or inference location is published. A GDPR Overview stated to cover where data is hosted exists behind an email request.
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.
The strongest certification stack in the lane, one tier short of full credit. The security page states SOC 2 Type 2 across all five trust services criteria — scope actually specified, which is rare — plus ISO 27001:2022 with the version named and ISO 42001. A trust centre exists at trust.ontra.ai on Vanta, is publicly linked from the security page, and states that it carries subprocessor information and offers subscription to change notifications. Two things hold this at B. No auditor is named and no coverage period or report date appears on any readable surface, and the trust centre body did not render to automated retrieval, so whether reports are downloadable, gated behind a click-through, or gated behind a sales conversation could not be established. Under the standing rule, where the access flow cannot be determined the lower tier is graded and the reason stated: that is why this is B and not A. No request was submitted. Read 1 September 2026.
A real trust centre and a scoped report, undercut by the vendor contradicting itself on whether it holds the certification. The trust centre states that a SOC 2 Type II report is independently issued and covers security, availability and processing integrity, which names the standard and its scope. But the same page's compliance section says the systems are aligned with SOC 2 Type II standards, and its summary strip reads SOC-aligned, while the support FAQ states the company is SOC 2 Type 2 certified. Alignment is self-assessment and certification is not, and the two cannot both be the position. The conflict is the finding and it is what prevents this reaching the top band, alongside three ordinary gaps: no auditor is named, no audit period or report date appears, and the report itself is reachable only by emailing the company's information security address, with the portal not stating whether that request fulfils without a sales conversation, so the lower tier is assumed. What keeps it above the band below is that these are not unsupported badges: a scoped, independently issued report is claimed to exist and a route to it is offered.
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.
The architecture is described in real detail and the providers behind it are never named. Ontra sets out its own pipeline layers by name, describing retrieval-augmented generation, query understanding and embedding, and states a zero-retention commitment at the model layer, so a buyer can see the shape of the system and knows customer content is not held by the model provider. What no readable surface answers is the question a buyer actually asks: whose model sees my content. No model, model family or provider is identified, and no inference location is stated. One further fact was established on 1 September 2026 and it cuts in the vendor's favour: the trust centre at trust.ontra.ai maintains a dedicated subprocessors page carrying a subscription for email notification of changes to the subprocessor list, so a change-notification mechanism exists even though the list itself could not be read. That page is a Vanta-hosted portal whose body renders client-side and returned only the page shell across repeated retrieval attempts, which is a limit on the reading rather than a gap in the disclosure, and nothing is graded against the vendor for it. B on the band's second limb, architecture described without the providers; an operator fetch of that page would settle whether the model providers are named there and, if they are, would move this row.
The vendor refers to advanced AI without identifying anything underneath it. The support FAQ says the platform deploys the most advanced AI solutions only where they can add value, which is a characterisation of the models rather than a disclosure of them. No model is named, no provider is identified, no version is given, no processing location for inference is stated, and no commitment to notify customers when any of it changes was located. Amazon Web Services is named and is not counted here: naming a cloud host establishes where the vendor's platform sits, not whose model reads a side letter, and the same fact is graded on the deployment row. One route to the answer exists and is closed: the trust centre lists a GDPR Overview stated to cover which subprocessors are involved, and its link resolves to a mailto address. A buyer can therefore establish that AI is used on their investor documents and nothing whatever about whose it is, which is the substance of this band.
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.
A real pricing page carrying tiers, feature splits, the unit of charge and one actual number. Contract Automation publishes three editions with a comparison matrix covering playbook customisation, who performs the work, turnaround and document management, and states a monthly minimum fee of $2,000 on both Advanced and Premier, with no monthly minimum on Standard. Insight for Funds publishes three tiers and Insight for Credit two, each with a populated feature matrix. Atlas, Accord, DDQ and KYC publish their licence inclusions and route the figure to Request Pricing. Free trials and a proof-of-value are offered without a sales gate on several products. B rather than A because the per-document rate that actually drives the bill is never published, so a buyer knows the floor but not the price, and six of the seven products carry no figure at all. B rather than C because a published figure exists at all, which C forbids.
No pricing information is published at any level, including the unit of charge. The site inventory taken from the navigation and footer on 4 September 2026 contains no pricing page, and the support page routes pricing explicitly to a sales conversation, listing a Sales contact for ProVision pricing, enterprise discussions and rollout planning behind a mailto link. Nothing states whether the platform is charged per matter, per fund, per side letter processed, per seat or as a firm-wide licence, and no tier structure, band, minimum, term or implementation cost appears. Two FAQ entries touch the commercial question, What is the ROI and What does a pilot look like, and both are collapsed accordions whose answers this instrument could not expand; neither is a pricing disclosure in any event. No pricing row is written, which is the correct outcome where the only thing published is an invitation to contact sales.
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.
Coverage is described by buyer and by workflow with real precision. The site publishes pages by team — legal, compliance, finance and investor relations — and by firm type, covering investment firms, investment banks and law firms, the last aimed at automating MFN processes. The practice scope is concrete and named: NDAs and other high-volume routine contracts, engagement letters, side letters and MFN elections, credit agreements and covenants, entity management and CTA compliance, reverse KYC, and investor due diligence questionnaires. The private markets framing is itself a genuine boundary and the vendor repeats it everywhere. B rather than A because the limits inside that boundary are not stated: nothing says which document types Contract Automation will decline, government use is not addressed, and the only scope caveat located is a pricing footnote noting that some document types such as commercial agreements or engagement letters run to a 48-hour rather than 24-hour turnaround.
The practice is defined with unusual precision and the boundary is not stated. The product is addressed to private investment funds lawyers and fund formation teams, and the work is named at the level of the task rather than the practice group: side letters, limited partnership agreements, master side letter compilation, most favoured nation elections and LP comment memos, described as post-close fund workflows. Segment is evidenced by the named customer set, which is elite and international, and geographic reach is published as the United States, United Kingdom, European Union, Hong Kong, Singapore and the Middle East. The buyer is also identified on both sides of the relationship, with the platform described as serving funds and law firms alike. What is missing is where the product stops. No statement identifies fund types or structures it does not support, nothing addresses whether an in-house fund legal team can buy it directly as against through counsel, no firm size floor is given, and the roadmap language about expanding into a unified platform for fund formation teams leaves the current edge of the product undefined.
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?
The security page states in its opening line that Ontra protects customer data by never using it to train models, and repeats the point as a headline commitment. No matching term was located in the published Terms of Service, and the Customer Agreement that clause 1 says supersedes those Terms is not published. Terms clause 6.2 runs the other way, reserving the right to collect usage data including on an aggregated and anonymized basis for improving products and services, except as limited by a Customer Agreement. Recorded as policy rather than contractual on that basis.
This silence is of neither ordinary kind. It is not an agreement that grants an improvement right without naming training, and it is not an agreement that grants none: it is a retrieval limit, recorded as such, on a vendor that addresses the question directly. The trust center and support pages both publish an FAQ entry headed Do you use our data to train AI models, so the position exists and is offered to buyers; the answers on both pages render as collapsed accordions that this instrument cannot expand.
The retrieval ladder was run and partly succeeded on the same pages: search recovered the answers to other entries from the identical accordion set, including the statement that the platform does not require AI to run and deploys advanced AI only where it adds value with guardrails, and the confirmation of single sign-on with multi-factor authentication, but not this one. The two documents that would settle it are gated, with the Data Processing Agreement and the Terms of Service both reachable only by emailing the company's information security address.
This row records what could be located as of 4 September 2026 and is expressly not a finding that ILS is silent on training or that it trains on customer content; the vendor publishes a heading this index could not open. Recovery of the answer or of either document would be applied as an amendment with its own date.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
Ontra publishes a Zero Data Retention commitment covering data provided to third-party LLMs through an Ontra application, which is processed only to deliver the service and deleted afterwards. The period is effectively stated as none at that layer and the customer is not offered a setting, which is why this is recorded as a disclosed fixed window rather than customer-configurable. The commitment is scoped to the model layer: no located material states how long documents, extracted obligation data or generated outputs are retained inside the platform itself, which is a repository product by design.
No retention period for uploaded documents, extracted provisions or generated outputs was located on any readable surface. The trust center describes how data is held rather than for how long, covering AES-256 encryption at rest, TLS 1.2 or higher in transit, single-tenant deployment with a dedicated instance per customer, role-based access control and redundant backups, and states that the customer owns its data. None of that is a retention position.
No default period, no configurable window, no deletion route and no certificate of destruction appears anywhere readable, and nothing addresses what happens to a fund's side letters at the end of a matter or of the subscription. The documents that would carry it are listed and gated: a Data Processing Agreement, a Privacy Policy and a GDPR Overview, each resolving to a mailto link. Searched the home page, the ProVision overview, the about page, the support FAQ and the trust center on 4 September 2026.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
No located public material addresses ethical walls, matter-level segregation or tenant separation. The security page, pricing page, AI capabilities page, Terms of Service and home page were checked on 1 September 2026. The closest material runs the other way: Terms clause 10.2 states that other Users with appropriate access rights may have access to a customer’s User Data. Atlas lists advanced user permissions as a license inclusion, and the MCP server is described as read-only, but neither is presented as a segregation control and no document describes how any boundary is enforced.
A separation model is documented rather than asserted, and the vendor makes it a positioning claim. The trust center states that most legal technology providers operate shared multi-tenant environments and that ProVision is different, being deployed within a secure single-tenant AWS environment logically segregated per customer, with each customer's documents and extracted data held in a dedicated instance and never commingled with other clients' data.
It lists no shared document storage across customers as a distinct control, alongside granular role-based access control limiting access to authorized users. That answers separation at the tenant level, which is the level a law firm buyer requires of a hosted platform. One limb below it is not addressed: nothing describes segregation between matters, funds or clients inside a single firm's instance, which is a live question on a product whose value is comparing provisions across investors and across matters, and no ethical wall or conflicts mechanism is described.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
The privacy policy states Ontra may access, preserve and disclose any information it stores to external parties where it believes in good faith that doing so is required or appropriate, giving law enforcement and national security requests and legal process such as a court order or subpoena as examples. The standard is Ontra’s own good-faith judgment and extends to what it considers appropriate, not only what is legally required.
No commitment to notify the customer, and no carve-out for notice where lawfully permitted, was located on 1 September 2026. The policy does commit to reasonable efforts to notify before a change of control, which is a different event.
Nothing located addresses compelled disclosure or customer notice in either direction. The evidence home for this signal is the confidentiality section of a master agreement or the law enforcement section of a privacy policy, and neither is readable: the Terms of Service and the Data Processing Agreement are listed on the trust center behind mailto links, and the Privacy Policy appears both behind the same gate and at a public footer URL that was not opened in this pass.
No transparency report, government request statement or disclosure practice appears on the home page, the ProVision overview, the about page, the support FAQ or the trust center body, all read on 4 September 2026. The nearest adjacent statement runs to access rather than disclosure, with the trust center asserting a zero-knowledge framework under which ILS cannot access customer provisions or investor data; that claim, if it holds, would bear on what the company could produce under compulsion, but it is not a notice commitment and nothing published connects the two.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
The product does not retrieve primary law, so there is no legal corpus to source. Ontra’s AI operates on the customer’s own fund documents, side letters, credit agreements and playbooks, plus the Ontra Market Playbook used as a negotiation baseline. No public material identifies any primary law source, license basis or update cadence, checked on 1 September 2026. Recorded as not addressed because the question does not arise for this product class rather than because the vendor declined to answer it.
The inputs are named and they are the customer's own documents rather than any licensed corpus. Published material describes the platform working from uploaded side letters, limited partnership agreements, related documents and existing master side letters, with provisions structured from them while the original legal text is preserved. There is no external body of content: the product does not retrieve primary law, published precedent, a market-standard clause bank or any third-party dataset, and none is named on any surface.
The one place a corpus question could arise is the comparison and merge feature, which surfaces provision information across clients and matters, but that operates on the firm's own material rather than on licensed content. There is accordingly no licensing question of the kind this signal was written for and no jurisdictional coverage statement to record. Searched the home page, the ProVision overview, the about page, the support FAQ and the trust center on 4 September 2026.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
No citator, and none would apply. Ontra’s outputs are summaries, clause comparisons and obligation data drawn from the customer’s own agreements rather than from case law or legislation, so there is no authority whose subsequent history could be checked. Nothing on the AI capabilities, product or security pages addresses currency of underlying legal authority. Checked 1 September 2026.
Nothing on any located surface addresses checking authority for subsequent history, and the product does not retrieve or present primary law at all. ProVision reads investor side letters and fund documents and produces structured provisions, master side letter views and MFN election forms; no case, statute or regulation is surfaced to a user at any point in the published workflow. The question does not bite on this product class and the value records the honest absence rather than a shortcoming.
Searched the home page, the ProVision overview, the about page, the support FAQ and the trust center on 4 September 2026.
Refusal and Uncertainty Behavior
What does the product do when the answer is not in the corpus?
No located public material addresses what the product does when it cannot ground an answer. The security page describes subject-matter experts who review outputs and flag potential hallucinations, but that is human detection after generation rather than a documented abstention path in the product, and no confidence signal or no-answer behavior is described. The AI capabilities page, the product pages and the security page were checked on 1 September 2026. Notable because AI Search is marketed as answering questions across a firm’s full agreement set.
An assurance is published and no behavior is described. The support FAQ states that the platform provides fail-safes or guardrails to retain full control over outputs and prevent hallucinations, which addresses the topic in the abstract, and two design controls sit alongside it: extraction preserves the original legal text, and comparison is said to operate without breaking traceability, so a reviewer can return to source.
None of that describes what the system does when it cannot ground an output. No abstention state, no no-answer condition, no confidence or certainty score against an extracted provision, and no described handling of the ordinary failure conditions for this product class is published, and those conditions are specific and foreseeable here: an ambiguous or hand-amended side letter, a scanned execution copy, a provision that spans clauses, or two investor terms that conflict.
A claim to prevent hallucinations is an assertion about the outcome rather than a description of the behavior, and is recorded in this summary rather than credited as one.
Fabricated Citation Record
Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?
No court order, opinion or disciplinary record naming this product has been located. The AI Hallucination Cases database maintained by Damien Charlotin was searched on 1 September 2026 on the product name and on the former company name InCloudCounsel, alongside general sanctions coverage, and nothing naming the product was found. This is a statement about the public record rather than a finding about the product. Ontra’s outputs are contract and fund-document work product rather than citations to legal authority.
The AI Hallucination Cases database maintained by Damien Charlotin was searched on 4 September 2026 on the product name ProVision and on the company names Intelligent Legal Solutions and ILS. No court order, opinion or disciplinary record naming the product or the company was located. This records the state of the public record on that date and is not a finding about the product. The signal also sits at an angle to this product class, since ProVision structures negotiated investor terms rather than generating legal citations, so a fabricated citation is not the failure mode it would ordinarily produce.
Bar Guidance Alignment
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. ABA Formal Opinion 512 is not mentioned and no state bar or overseas regulator opinion is named across the home page, AI capabilities page, security page, pricing page or Terms of Service, checked 1 September 2026. Terms clause 12.2 states Ontra is not a law firm and forms no attorney-client relationship, which is a positioning statement rather than engagement with the guidance its buyers and its own legal network members are bound by.
No bar authority, regulator, conduct rule or ethics opinion is named on any located surface. Nothing on the home page, the ProVision overview, the about page, the support FAQ or the trust center engages professional regulation, and no jurisdiction-specific guidance is mapped. The absence is more consequential than it would be on a domestic product because the company reports operating across the United States, United Kingdom, European Union, Hong Kong, Singapore and the Middle East, which carry materially different regimes for the use of technology on client matter material and for cross-border handling of it.
The nearest published language addresses professional judgment rather than professional rules, with the about page stating that the technology assists rather than second-guesses professional judgment. The Terms of Service, which is where a jurisdiction or conduct provision would ordinarily sit, is available only by emailing the company.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
Public materials claim cost control and efficiency — outsourcing routine negotiations to control costs, decreasing entity management costs, and freeing teams for higher-value work — without addressing how AI-assisted work should be recorded or disclosed on a bill. The published pricing structure is the cost of the technology and service to the buyer, which under the standing rule is not what this signal tracks. No audit record of AI-assisted work and no fee or disclosure guidance was located on 1 September 2026.
Recovery and efficiency claims are published and nothing addresses the bill itself. The support and trust center FAQ frames the problem in explicitly billing terms, stating that manual transfer of side letters into Excel or Word compendia and manual MFN tracking results in hours billed that are not recovered by the firm, inaccurate work product and slower delivery, and a further collapsed entry is headed What is the ROI.
So the pitch is that the firm captures fees it currently loses. What is absent is everything this signal asks for: no per-matter record of AI-assisted work is described as available, no guidance on fee or disclosure treatment is published, and nothing states whether a provision extracted or structured by the model is identified as such to the firm or to the fund client whose matter it is. The direction is worth recording, since it is the second record in this pull to run the opposite way to the compression this signal was written to catch: the stated effect is recovering unrecovered hours rather than reducing them.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
A subprocessor list is published on Ontra’s trust center at trust.ontra.ai, which also invites subscription to email notifications when subprocessors change. The portal is publicly linked from the security page and no agreement or sales conversation was required to reach it. Its body did not render to automated retrieval on 1 September 2026, so the contents of the list were not read and it is not assumed that model providers appear on it; no model provider is named anywhere on the readable site. Recorded on the existence of the published list and its change-notification mechanism.
The artifacts a firm would need exist, are named individually, and every one of them is behind an email request. The trust center's Resource Vault lists a Data Security White Paper described as a technical deep dive into architecture, encryption and the zero-knowledge framework; a GDPR Overview stated to cover where data is hosted and which subprocessors are involved; an independently issued SOC 2 Type II report; a Privacy Policy; a Data Processing Agreement setting out the company's role as processor; and an Incident Response Overview.
Each View link resolves to a mailto address at the company's information security team, and the portal does not state whether the request fulfills without a sales conversation. That is precisely this value: the material exists and is reachable only by asking. It does not reach the rung above, because no subprocessor or model provider is named anywhere in the clear, so a firm cannot answer a client's AI clause from published material alone.
The only external link in the vault points to the California Attorney General's own CCPA page rather than to any ILS document.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
No located public material addresses court disclosure or AI-use certification. Nothing describes an exportable record of which model produced which passage or who verified it, checked across the AI capabilities, product, pricing and security pages on 1 September 2026. Insight publishes side-letter compliance exports and Ontra cites an SEC production at Linden Capital Partners, but both are regulatory and investor reporting artifacts rather than a filing disclosure record. The product serves fund legal and compliance teams rather than litigators, so the question rarely arises in practice.
An audit record is published as a product feature and nothing states that it distinguishes model work from human work. The home page commits to keeping a clear, complete record of every action, approval and document version to support compliance, and the overview describes comparison and structuring operating without breaking traceability, with the original legal text preserved so an entry can be traced to its source clause.
That is a real record of what happened to a document and who approved it, which is more than most records in this corpus publish. What is absent is the AI-specific half. Nothing says the record identifies which provisions were extracted by the model rather than entered by a person, no model or version is attributed to an output, and nothing describes exporting that history for a client audit, a regulator or a court. Exports that are described are of work product, being MFN election forms in PDF and Word with built-in anonymization, rather than of the audit trail.
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.
- Primary Law Corpus Provenance
- Good Law Verification
- Refusal and Uncertainty Behavior
- Bar Guidance Alignment
Which one fits
Choose Ontra if
- You want AI governance you can point to on paper. Ontra holds ISO 42001 for its AI management system, SOC 2 Type 2 across all five trust services criteria and ISO 27001:2022, and runs a trust center with a subprocessor list and email alerts on changes.
- You want more than side letters from one vendor. Ontra covers outsourced NDA and contract negotiation, entity management and structure charts in Atlas, obligation tracking in Insight, investor questionnaires and reverse KYC, and names Blackstone, AllianceBernstein and Battery Ventures among users.
- You want your own AI tools to reach entity data. Ontra's MCP server gives a firm's own language model real time, read only access to Atlas entity and ownership data, and Ontra for Word puts the product inside the drafting surface lawyers already use.
Choose ProVision if
- Your firm will not accept shared infrastructure for client documents. ProVision runs each customer in a dedicated single tenant AWS instance, states that documents and extracted data are never commingled with other clients' data, and offers configurable data residency.
- You run fund formations and need MFN elections done end to end. ProVision builds a master side letter view from uploaded side letters and partnership agreements, generates investor specific election forms in PDF and Word with anonymization, and tracks responses into one record.
- You want a tool used by firms like yours. ProVision names Cleary Gottlieb, Fried Frank, Goodwin, Paul Weiss, Proskauer, Ropes & Gray and Willkie Farr & Gallagher, and reports more than 5,000 side letters across over 450 matters in 2025.
In summary
Ontra
Ontra, from Ontra, LLC, is an AI platform for private markets firms covering outsourced negotiation of NDAs and other routine contracts, entity management in Atlas, obligation and side letter tracking in Insight, investor questionnaires and reverse KYC. Its AI turns fund documents into structured data, summaries and clause comparisons, with subject matter experts reviewing outputs, and on contract negotiation the work is done by contract professionals or lawyers depending on the edition. The AI Legal Index grades it in the top two bands on twelve of fifteen capability axes. It holds ISO 42001, SOC 2 Type 2 and ISO 27001:2022 and states more than 1,000 private markets firms as users. As of 1 September 2026 the index located no named model provider, hosting region or per document price.
ProVision
ProVision, from Intelligent Legal Solutions Limited of London, founded in 2024 by former investment funds lawyers from Goodwin and Proskauer, is a side letter and most favored nation management platform for fund formation lawyers. It extracts provisions from uploaded side letters and partnership agreements while preserving the original text, builds a master side letter view, and runs MFN elections end to end. The AI Legal Index grades it in the top two bands on seven of fifteen capability axes. It runs each customer in a dedicated single tenant AWS instance and names Cleary Gottlieb, Fried Frank and Ropes & Gray among customers. As of 4 September 2026 the index located no readable customer agreement, named model provider, integration or price.
Questions buyers ask
Ontra vs ProVision: which is better for side letter and MFN management?
On published evidence Ontra sits in the top two bands on twelve of fifteen AI Legal Index capability axes and ProVision on seven of fifteen, identical on seven. Ontra publishes more on AI governance, security and pricing across a wider private markets platform. ProVision is a dedicated side letter tool with single tenant hosting and named elite law firm customers. Fund formation teams at law firms will find ProVision built for their exact task.
Does ProVision use AI on side letters?
Yes, where it adds value. ProVision says its platform does not require AI to run, and that it deploys AI where useful with guardrails to keep control of outputs with the lawyer. Extraction structures provisions from uploaded documents while preserving the original legal text, and comparison keeps traceability to the source clause. No model or provider is named. Graded by AI Legal Index against 15 capability axes and 12 legal signals, including privilege handling and citation accuracy, from each vendor's own published materials, verified September 26, 2026. No vendor pays for placement.
Does Ontra train AI on client data?
Ontra's security page states that it never uses customer data to train models, and that data passed to third party language model providers is processed only to deliver the service and deleted afterwards. Its public terms reserve use of usage data, aggregated and anonymized, to improve its products, except as limited by a customer agreement, which is not published. ProVision's answer could not be read. Graded by AI Legal Index against 15 capability axes and 12 legal signals, including privilege handling and citation accuracy, from each vendor's own published materials, verified September 26, 2026. No vendor pays for placement.
How much do Ontra and ProVision cost?
Ontra's contract negotiation service publishes a monthly minimum of $2,000 on its Advanced and Premier editions and none on Standard, without a per document rate; its other products route to a quote. ProVision publishes no price, tier or unit of charge, and directs pricing questions to its sales team by email. Graded by AI Legal Index against 15 capability axes and 12 legal signals, including privilege handling and citation accuracy, from each vendor's own published materials, verified September 26, 2026. No vendor pays for placement.
What do Ontra and ProVision both leave unpublished?
Whose model reads the fund documents, and how accurate it is. Neither names a model provider on a readable page, and neither publishes an accuracy figure or error rate for its extraction. Neither states how long documents and outputs are kept inside the platform, and neither names bar guidance on AI or offers a record separating AI extracted provisions from human edits. Graded by AI Legal Index against 15 capability axes and 12 legal signals, including privilege handling and citation accuracy, from each vendor's own published materials, verified September 26, 2026. No vendor pays for placement.
Three readings to weigh. Ontra's public terms reserve use of usage data, aggregated and anonymized, to improve its products, alongside a security page statement that it never trains models on customer data; the customer agreement that replaces those terms is not published. ProVision's trust center calls its SOC 2 Type II report independently issued and also calls its systems SOC 2 aligned, and its terms, data processing agreement and training answer could not be read, so its low grades record a gated estate. Ontra was verified on 1 September 2026 and ProVision on 4 September 2026. Neither vendor reviewed this page.
Neither vendor paid for inclusion, placement or a grade, and neither reviewed this page before it published. Everything above comes from public material on the dates shown. How the index grades.