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Wisedocs

Wisedocs is an AI medical record review platform for claims work, sold to insurance carriers, third-party administrators, independent medical evaluators and law firms. It takes unstructured claim files, medical records, legal forms and insurance documents, including faxes, scans and handwritten notes, and sorts, indexes and deduplicates them, separates co-mingled claimants, builds chronologies by date, provider and event, and generates medical summaries structured for causation and liability with every fact hyperlinked to its source page; red flags surface delayed care, timeline gaps and contradictions, WiseChat answers questions about a file, and custom reports assemble verified data for adjusters, evaluators and attorneys. Every summary passes through human-in-the-loop validation by trained reviewers before the user is notified it is ready, and the vendor states its models are trained on more than a hundred million documents. The company is Wisedocs AI of Toronto, founded in 2021, which closed a 12.7 million Canadian dollar Series A in 2024 led by Information Venture Partners with Thomson Reuters Ventures and a further 4.5 million in growth capital from CIBC; it states SOC 2 Type II compliance achieved in August 2024 with no findings and HIPAA compliance, offers multi-tenant SaaS, private cloud, on-premise and hybrid deployment with regional model hosting for data residency, and has published a medical long-context reasoning benchmark, MLCR, with an independently run edition through Artificial Analysis. Its legal-market pages address defence lawyers, claims legal teams and medical-malpractice litigators, and pricing is by demo.

Vendor siteToronto, Ontario, Canada
Last verifiedSeptember 6, 2026
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Capability grades

All 15 axes, graded from public sources on the date shown. Hover a grade to see what the letter means on that axis.

AA on AI CentralityThe artificial intelligence is the product. Remove the models and there is nothing left to sell.

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 machine learning is the mechanism the buyer pays for. The product reads unstructured medical and claims files and produces sorted, indexed, deduplicated chronologies and cited summaries with red flags; the human validation layer checks the model's output rather than producing its own, and the vendor's founding product in 2023 was the AI medical summaries platform. Remove the models and there is a document store and a review queue. Home page, medical summaries page and 2025 WiseChat release read 6 September 2026.

Source: Vendor Published
BB on Citation Accuracy and Hallucination DisclosureGrounding is real and documented, with linked primary sources and a described retrieval method, short of published accuracy figures an outsider can test.

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.

Grounding is real and documented with links to source, and a benchmark exists, short of a published accuracy figure for the product itself on the surfaces read. Every summary is stated to be hyperlinked to its original document with citations at the fact level, and each summary passes human-in-the-loop validation before release; the home page states the company released the Medical Long Context Reasoning benchmark to measure how models reason across long fragmented medical records and an independently run edition with Artificial Analysis, which is a testing regime, but the benchmark page was not opened and whether it reports Wisedocs' own product accuracy is not established. The FAQ answers the accuracy question qualitatively. The benchmark page is the rebuttal route to A. Medical summaries page, home page and FAQ read 6 September 2026.

Source: Vendor Published
AA on Autonomy and Oversight ModelWhat the system runs alone, what constrains it, and how a lawyer checks it are all published: modes, thresholds, review surfaces, and the route a matter takes back to human judgement.

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.

What runs alone, what a person must validate, where the review sits and what constrains it are all published. Modes: sorting, indexing, deduplication and co-mingled claimant detection run automatically; every medical summary passes through human-in-the-loop validation by trained expert reviewers before release. Review surface: users are notified when verified documents are ready for final review, every fact is cited to its source page, and activity logs track actions. Constraints: review templates turn the customer's case strategy into the focus of the review, and the enterprise page states explainable models and audit trails. Route back: the customer's own final review sits after the expert validation. Nothing states a confidence threshold below which a summary is held back, which is the one limb short. Medical summaries page, enterprise page and claims legal page read 6 September 2026.

Source: Vendor Published
CC on Operational and Outcome EvidenceCustomer logos and unattributed testimonials stand in for evidence, or results are quoted with no basis stated.

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.

Figures without a named customer on the surfaces read. The home page states sixty to eighty per cent faster first touch and up to three times lower manual review cost, the medical summaries page up to seventy per cent faster record reviews, and a careers listing eighty-five per cent time and fifty-five per cent cost reduction, all unattributed; the vendor states a customer base that more than doubled at its 2024 raise. A customer stories section exists in the navigation and was not opened, and is the rebuttal route. Home page, product page and release read 6 September 2026.

Source: Vendor Published
BB on Privilege and Confidentiality PostureSubstantive published commitments on confidentiality and training use, short of the full picture: commonly silence on segregation between users or matters, or on what the underlying model provider may retain.

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 published commitments on segregation and deployment, with an adverse training position stated and privilege not named. Segregation at the level an in-house or firm buyer requires: role-based access, SAML single sign-on, SCIM provisioning, activity logs and data access safeguards, with private cloud, on-premise and hybrid deployment available. Training: the enterprise page states anonymised training methods and the vendor states models trained on more than a hundred million documents, which is a published position that customer content trains after anonymisation, with no agreement located either way. Third-party providers: regional model hosting is offered without naming the providers. Retention and deletion: not located, and no customer agreement was located. Nothing addresses privilege or work product for a product whose legal buyers use it to build causation and liability arguments. Enterprise page and product pages read 6 September 2026.

Source: Vendor Published
CC on UPL and Professional Responsibility PostureA boilerplate disclaimer sits in the terms while the marketing describes the product in advice terms, or the intended audience is left ambiguous.

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.

No advice line or supervision statement was located. The defence-lawyer, claims-legal and malpractice pages sell the product to attorneys and paralegals as producing defensible, audit-ready documentation, and the human-in-the-loop design is described in terms of clinical accuracy; no surface read states that summaries are not legal or medical advice, who should rely on them, or how the product supports a supervising lawyer's duties, and no customer agreement was located to carry such a statement. Role pages and product pages read 6 September 2026.

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

AI Governance and Bias Disclosure

Published governance over model behaviour: who owns it inside the vendor, what is tested before release, and what is disclosed about disparate output across matter types, parties, or populations.

A published governance statement with real mechanisms and a testing programme, short of a named owner or bias findings. The enterprise page's AI Governance section states human-in-the-loop validation, audit trails, explainable models and anonymised training methods as the basis for ethical, accurate and accountable AI, and the company has published the Medical Long Context Reasoning benchmark with an independently run edition through Artificial Analysis, which is a public testing regime for the class of models it uses. No ISO 42001 or equivalent certification, no accountable owner and no statement about uneven output across record types is published on the surfaces read. Enterprise page and home page read 6 September 2026.

Source: Vendor Published
CC on AI Safety and Data StewardshipA generic privacy policy covers the product without addressing what happens to documents and prompts after processing.

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.

Some of the ground is covered and the rest was not located. Access control: role-based access, SAML single sign-on, SCIM provisioning, full activity logs and data access safeguards on the enterprise page, with SOC 2 Type II and HIPAA compliance stated. Not located: a retention period, a deletion commitment, a sub-processor list or an incident-notification practice; no customer agreement, DPA or trust centre was located on the surfaces read, and the privacy policy was not opened and is the rebuttal route. Enterprise page and product pages read 6 September 2026.

Source: Vendor Published
DD on AI Liability and RecourseNothing published on who bears the loss when the system is wrong.

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.

No liability position was located on the surfaces that could be read. Product, role, enterprise and use-case pages describe defensibility of outputs without any indemnity, cap, warranty or insurance position, and no terms of service or customer agreement surfaced in search or in the material read; the site footer was not inventoried, so whether an agreement exists is not established. This records what is locatable on the date and not a finding that no position exists; any published agreement is the rebuttal route. Surfaces read 6 September 2026.

Source: Operator Verified
CC on Practice Systems Integration DepthIntegrations are listed as logos or marked as coming, with no documentation an implementer could use.

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.

Integrations are referred to without documentation an implementer could use on the surfaces read. The enterprise page describes disconnected systems as the problem the platform solves and offers SAML and SCIM identity integration, and the platform accepts drag-and-drop upload of PDFs, faxes and images; no claims system, case management platform or document management integration is named with what moves and in which direction, and no integrations page was opened. Enterprise page and product pages read 6 September 2026.

Source: Vendor Published
AA on Deployment Model and Data ResidencyDeployment options and data residency are published, including the regions available, what changes between tiers, and where processing happens as distinct from where data is stored.

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.

Deployment options are published with tenancy, residency and model-processing location. The enterprise page states that Wisedocs is offered as multi-tenant SaaS, private cloud, on-premise or hybrid deployment, that regional model hosting is supported to meet data residency requirements, and that high-availability architecture underlies the enterprise tier; that answers who shares infrastructure, where data sits and where the models run. Specific regions are not enumerated. Enterprise page read 6 September 2026.

Source: Vendor Published
BB on Security Certifications and Trust CenterCertification is real and stated, short of accessible evidence: a named standard without scope, date, or a way to obtain the report.

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.

Certification is real and dated, short of a report reachable without asking. The vendor announced SOC 2 Type II compliance on 13 August 2024 with zero findings across security, availability, processing integrity, confidentiality and privacy, and states HIPAA compliance across its role pages. No auditor, coverage period, report route or trust centre is stated on the surfaces read. SOC 2 announcement and role pages read 6 September 2026.

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

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 supply chain is partly disclosed. The vendor states its models are domain-trained on more than a hundred million documents, that regional model hosting is available so inference can be placed by residency requirement, and that its MLCR benchmark evaluates frontier closed- and open-weight models, which implies third-party models in the stack; no provider or model is named and no change-notification commitment is stated. Enterprise page, home page and directory description read 6 September 2026.

Source: Vendor Published
DD on Commercial TransparencyNo pricing information published at any level, including the unit of charge.

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.

No pricing information was located at any level. The site offers a demo and a call to discuss claims workflows, and no unit of charge, tier, figure or pricing page appears in the material read; the footer was not inventoried, so the absence of a pricing page is not established by inventory and this row is rebuttable on one if it exists. Home page, product and enterprise pages read 6 September 2026.

Source: Operator Verified
BB on Firm and Practice CoverageSegment and practice coverage is described with substance, short of the boundaries: what is supported is clear, what is not is left open.

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.

Segment and coverage are described with substance and the boundaries are partly stated. The vendor names workers' compensation, auto and casualty, disability, liability, healthcare, legal defence, government and IME and QME claims as supported review types, role pages for defence lawyers, claims legal teams, claims adjusters and evaluators, a malpractice use case with files exceeding a hundred thousand pages, and North American operation. The legal pages are written for the defence side, which is a stated orientation; no jurisdiction or record type is named as unsupported. Home page, role pages and use-case page read 6 September 2026.

Source: Vendor Published

Legal Signals

What each signal means

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.

Confidentiality and Privilege

Client Data in Training

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

Permitted, in policy only

Public material states that customer content trains, refines or personalises models, with no matching term located in the published agreement. Any de identification, anonymisation or aggregation qualifier is recorded in the summary.

Public material states that training occurs on anonymised data, and no matching term was located in a published agreement. The enterprise page's AI Governance section lists anonymised training methods among the platform's controls and the vendor states its models are trained on more than a hundred million documents, which together state that customer content trains after anonymisation; no customer agreement, terms of service or DPA was located on the surfaces read to bind or contradict the statement. The anonymisation qualifier is the vendor's own. Surfaces checked 6 September 2026.

Source: Vendor Publishedexplainable models, and anonymized training methodsAs of Sep 6, 2026Evidence

Prompt and Output Retention

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

Not addressed

No located public material states how long prompts and outputs are retained.

No located public material addresses how long uploaded records, WiseChat prompts or generated summaries are retained. The enterprise page addresses access control and deployment without a retention period, no customer agreement was located, and the privacy policy was not opened and is the rebuttal route. Surfaces checked 6 September 2026.

Source: Operator VerifiedAs of Sep 6, 2026

Ethical Walls and Matter Segregation

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

Own model, documented

The product maintains its own permission model, documented, requiring the firm to keep it aligned.

The product maintains its own permission model and documents it at the level of a description. The enterprise page states role-based access controls, SAML single sign-on, SCIM provisioning, full activity logs and data access safeguards so that only the right people see sensitive information, and the product separates co-mingled claimants within a file; private cloud and on-premise deployment separate one customer from another entirely. Nothing describes how WiseChat's retrieval respects those permissions across claim files. Surfaces checked 6 September 2026.

Source: Vendor PublishedWisedocs supports role-based access controls (RBAC), SAML-based SSO, and SCIM provisioningAs of Sep 6, 2026Evidence

Third Party Request and Subpoena Notice

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

Not addressed

No located term or policy addresses third party requests for customer data.

No located public material addresses whether the customer is told when its data is demanded by a third party. No customer agreement or DPA was located on the surfaces read, and the privacy policy was not opened and is the rebuttal route. Surfaces checked 6 September 2026.

Source: Operator VerifiedAs of Sep 6, 2026
Accuracy and Authority

Primary Law Corpus Provenance

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

Not addressed

No located public material identifies the corpus behind the product’s answers.

No located public material identifies a legal corpus behind the product's output, and the product is not built on one: it summarises the customer's own medical and claims records and cites its findings to those pages, and the models are described as trained on claims documents rather than law. Product pages checked 6 September 2026.

Source: Operator VerifiedAs of Sep 6, 2026

Good Law Verification

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

Not addressed

No located public material addresses whether authority is checked for subsequent history.

No located public material addresses whether authority is checked for subsequent history, and the product does not retrieve or cite primary law; its output is medical chronologies and summaries. Recorded as the honest value for a product without a citator function. Surfaces checked 6 September 2026.

Source: Operator VerifiedAs of Sep 6, 2026

Refusal and Uncertainty Behaviour

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

Documented

The vendor describes refusal or abstention behaviour in public materials.

An explicit path for outputs that are not yet reliable is described: every medical summary is held for human-in-the-loop validation by trained reviewers and the user is notified only when verified documents are ready, and the product flags missing records, gaps and conflicting narratives rather than filling them. The behaviour is described rather than demonstrated, and no confidence threshold at which the model itself declines is stated. Medical summaries page and claims legal page checked 6 September 2026.

Source: Vendor PublishedEach medical summary is reviewed through human-in-the-loop validationAs of Sep 6, 2026Evidence

Fabricated Citation Record

Does a public court record exist involving output from this product?

None located

No court order, opinion or disciplinary record naming this product has been located as of the date shown. This is a statement about the public record, not a finding about the product.

No court order, opinion or disciplinary record naming Wisedocs was located as of 6 September 2026. The AI Hallucination Cases database maintained by Damien Charlotin was searched on the name together with a general search for court findings on AI medical summaries; results returned sanctions involving general-purpose chatbots, including a December 2025 Mississippi matter on fabricated deposition quotations that names no product, none of which is this vendor. This is a statement about the public record, not a finding about the product; a tool whose summaries are used in litigation carries a real exposure on fabricated facts rather than fabricated citations, and the check is worth repeating at re-verification.

Source: Operator VerifiedAs of Sep 6, 2026Evidence
Professional Responsibility

Bar Guidance Alignment

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

Not addressed

No located public material engages with bar or ethics guidance.

No located public material names an ethics opinion, bar rule or professional responsibility framework. The legal-market pages address defensibility and audit readiness, and the enterprise page states an AI governance position, but no guidance from any bar or regulator on lawyers' use of AI is named on the surfaces read. Role pages and enterprise page checked 6 September 2026.

Source: Operator VerifiedAs of Sep 6, 2026

Billing and Fee Posture

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

Savings claims only

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.

Law firms are a named buyer segment and the published position on the bill is a savings claim: manual review cost cut by up to three times, first touch sixty to eighty per cent faster, and record reviews up to seventy per cent faster. Nothing addresses how AI-assisted record review is recorded or disclosed on a client's bill or, for the insurer buyers, whether AI review cost is passed through to a claim. Home page and product pages checked 6 September 2026.

Source: Vendor Publishedreduce the cost of manual claim review by up to 3×As of Sep 6, 2026Evidence

Outside Counsel Guideline Readiness

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

Not addressed

No located public material supports a client side disclosure obligation.

No sub-processor list, model provider list or forwardable disclosure material was located. The enterprise page states regional model hosting and anonymised training without naming any provider, no DPA or customer agreement was located, and the privacy policy was not opened and is the rebuttal route. Surfaces checked 6 September 2026.

Source: Operator VerifiedAs of Sep 6, 2026

Court Disclosure Support

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

Partial record

Some elements of the record are available, short of a document level export.

Some elements of a verification record are available and no export of an AI-use record is described. Every summary carries fact-level citations to source pages, each summary is validated by a trained reviewer before release, and the enterprise page states audit trails and explainable models, which together record what was found and that a person checked it; nothing states that a record of the model used and the reviewer's verification can be exported for a court, and the vendor markets the outputs as defensible rather than as certified. Defence-lawyer page and enterprise page checked 6 September 2026.

Source: Vendor PublishedEach summary includes citations linked to the original documents—making it easy to support every claim with source-level proofAs of Sep 6, 2026Evidence
Contact

Correct a record, or ask how something was graded

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

AI Legal Index

The AI Legal Index is an independent index that tracks changes to AI vendors in legal. It holds 61 vendors across 9 categories, each graded on the same 15 capability axes and recorded against 12 legal signals, from public sources. No vendor pays for inclusion, placement, or rating.

Index Status
Last index update
September 6, 2026
The AI Legal Index is an editorial reference. It is not a regulatory body, not a law firm, and nothing published here is legal advice or a recommendation to retain or avoid a vendor. Records are verified against published sources, bar guidance and public court records. Where a record reads not addressed, the material was not located in public sources on the date shown. See the Methodology page for evaluation standards and limitations.
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