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Counsel Stack
Counsel Stack is a deep legal research platform for US law firms, built on what the vendor calls a fleet of specialized research language models for particular practices and jurisdictions, with an emphasis on structured citation verification. It synthesizes federal, state and local doctrine and positions itself for highly technical, boutique, cross jurisdictional and multi doctrine questions. It automatically saves research, conversations, sources, proof of citation verification and time entries.
Access is limited to US licensed attorneys, verified at signup, with no credit card required and API access on request. Founded in 2023, it placed first among all participants in the 2025 Vals Legal AI Report legal research study. The company also runs separate legal marketing, lead generation and web design businesses; only the research product is covered here.
Counsel Stack, head to head
Side by side on the same 15 capability axes and 12 legal signals: where the two part company, and what neither one publishes.
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Similar is not the same, so check that each one does the job you need. No vendor pays for placement.
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Ordered by how closely the graded profiles match across the 15 capability axes, inside the same categories. See how each axis is graded in the methodology.
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.
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.
For the research product, the AI is the product. The vendor describes a fleet of specialized research language models built by its attorneys, engineers and legal professionals for particular practices and jurisdictions, and the evaluator independently confirms multiple specialized models built for legal research. Retrieval, synthesis and citation verification are all model driven. The company's legal marketing, lead generation and web design businesses have nothing to do with AI and are separate from the research product the benchmark measured.
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 measured independently. In the 2025 Vals Legal AI Report legal research study, Counsel Stack placed first among all participants on all three criteria, ahead of every other legal AI product, a generalist model and the lawyer baseline: 81 percent accuracy against a 71 percent lawyer baseline, 77 percent authoritativeness against 68 percent, 71 percent appropriateness against 60 percent, and a 78 percent weighted score against 69 percent.
It answered 196 of 200 questions, with four technical timeouts the evaluator published with the scores. The evaluator set the rubric and weights in advance and Am Law 100 firms supplied the questions, so the figures can be checked on the evaluator's own site. The product also ships structured citation verification, saving proof of verification automatically in the research record. The evaluator found that all systems struggled with multi jurisdiction questions and did worse than a generalist model on fifty state statutory surveys.
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.
Autonomy is present, and oversight is implied by record keeping rather than described as a control. The product automatically saves research, conversations, sources and proof of citation verification, so a supervising lawyer can reconstruct what was done, and a published customer account describes the tool helping a small team rather than replacing people. Reconstructing work afterward is transparency, not a control point.
Searched the vendor site, deep research product page and third party coverage and found nothing on what the system does unaided, when it stops or escalates, what a lawyer must review before output is used, or what the vendor commits to when output is wrong. A traceability feature does not amount to oversight.
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.
Testimonials stand in for deployment evidence, though they are specific about the practice. Published accounts describe a solo attorney working with one other attorney, a paralegal and an intern who replaced their practice management software and use the product for research, and a legal content creator using it for Pennsylvania and federal law. These are real descriptions of use, honest about very small firm size. Searched the vendor site, product pages and third party coverage and found no named organization with figures, a date or a method. The independent benchmark measures test performance, not production outcomes.
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.
Searched the vendor site, the deep research product page and third party coverage, and ran targeted searches for a Counsel Stack security page, privacy policy or trust center without reaching one. Nothing is published on how client confidences are handled: no statement on training, no retention or deletion terms, no segregation model, no treatment of attorney client privilege or work product. The product saves research, conversations and sources by design, so material accumulates in it, and no published terms attach to that material.
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 position is enforced as a product gate rather than stated as a disclaimer. Access is limited to US licensed attorneys, verified at signup, and the vendor says only US licensed attorneys qualify at this time, so a nonlawyer cannot get the tool. That sets who may hold the product but not what the lawyer remains responsible for: searched the vendor site and product pages and found nothing on competence or supervision duties, the advice line, or jurisdiction limits within the United States, though the product spans federal, state and local doctrine.
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.
Agreeing to independent measurement and to publication of the results is the governance act here. Counsel Stack was one of four systems evaluated and named in the Vals legal research study, where the evaluator and trade press both reported that major vendors declined and at least one took part but then withheld permission to publish. Allowing publication of results that included four technical failures is a real accountability position, but it is a one time evaluation, not a management system.
Searched the vendor site, product pages and third party coverage and found no AI governance framework, AI management certification, named owner of model governance, testing regime before release, or anything on uneven output across matter types, parties or populations.
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.
Searched the vendor site, the deep research product page and third party coverage, and ran targeted searches for a security page or trust center without reaching one. No retention period, no deletion control, no access control detail, no encryption statement, no hosting disclosure, no subprocessor list and no incident or breach notification practice is published. The gap is sharpened by the product's own design: it automatically saves research, conversations, sources and timekeeping entries, so it accumulates a durable record of a lawyer's work with no published terms governing that record.
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 published indemnity, liability cap, carve out, warranty on output or insurance position is published, and no customer terms of service is published as published on the property. Recorded as a pure absence on the surfaces reached. Worth naming the shape of it: this vendor's entire positioning rests on measured accuracy and structured citation verification, and it publishes nothing about who bears the loss if a verified citation is wrong.
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.
Integration routes exist and none is documented. API access is offered on request, and a customer account describes the product replacing their practice management software, which suggests matter and time tracking built into the product rather than connected to it. Searched the vendor site, product pages and third party coverage and found no integrations page, no named connector for document management, practice management, court filing or Microsoft Word, and no API documentation available without contacting the vendor.
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.
Searched the vendor site, deep research product page and third party coverage, and ran targeted searches for infrastructure or security documentation without finding any. Nothing was found on deployment: no tenancy statement, hosting provider, region, residency option or processing location. The product is evidently cloud delivered and reached in a browser, but that is inferred from how it is sold, not stated.
Security Certifications and Trust Center
Independent attestation a buyer can pull without a sales call: SOC 2, ISO 27001, penetration test summaries, a trust center with current reports and named scope rather than a badge image.
Two targeted searches for the vendor's security page, privacy policy, terms, trust center or certifications found no vendor material. A failed search is weaker evidence than a page, so this shows that a buyer doing ordinary diligence would not find security material, not that none exists, and a single link could change it. The vendor publishes an independently measured accuracy score but nothing about how it handles data.
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 vendor describes its own model layer without identifying what sits underneath it. Published and independently confirmed: a fleet of multiple specialized research language models built for particular practices and jurisdictions, described by the vendor as assembled over years by its own attorneys, engineers and legal professionals. That tells a buyer the architecture is specialist rather than a thin wrapper. Searched the vendor site, the product pages and third party coverage and located no named foundation model or provider underneath that layer, no statement of where models run, no subprocessor list, and no commitment to notify customers when the supply chain changes.
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.
Real commercial terms are published at the entry point, but no rate is. A free tier can be reached without a sales conversation: the vendor says signup needs only a name and professional email and no credit card, with free trial access to its chat product. That is a published term and a self serve route. Searched the vendor site, product pages and third party coverage and found no rate for any paid tier, no unit of charge and no tier structure, with API access by contact request.
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 in substance, and the target is stated honestly. Scope is federal, state and local US doctrine, with specialized models claimed for particular practices and jurisdictions. The vendor positions itself narrowly, for highly technical, complex, boutique, cross jurisdictional and multi doctrine research, which says where it is strong rather than claiming to cover everything. Published customer accounts come from very small firms, and no enterprise scale is claimed.
Practice areas are not listed, state level coverage is not stated, and nothing says what the product does not cover; the measured weakness on fifty state surveys comes from the evaluator, not the vendor.
2 public documents
The public pages on file for Counsel Stack, with the recorded signals each one supports and the date it was last read. Open any of them and check the reading against the record.
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Prompt and Output Retention, Primary Law Corpus Provenance, Good Law Verification and 2 more
Read Aug 29, 2026
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Fabricated Citation Record
Read Aug 29, 2026
Legal Signals
What each signal meansA 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.
Client Data in Training
Can material a lawyer puts into this product be used to train a model?
A published agreement or policy exists and none of it addresses the question either way, or the document that would answer it could not be read and the summary names the retrieval limit. The summary states which shape the silence takes: an improvement right granted that never names training, or no improvement right granted at all.
Searched the vendor site, the deep research product page and third party coverage on 29 Aug 2026, and ran targeted searches for a Counsel Stack privacy policy, terms of service or security page without reaching one. No located material states whether customer content may be used to train models, either way. Recorded as silent under the rule that a value is never inferred from the absence of a contradiction. The question carries weight here because the vendor states it has assembled its own specialized models over years, so a buyer would want to know what went into them and whether their own research contributes.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
Retention is acknowledged in public materials with no stated period.
Retention is a product feature with no period attached. The vendor says the product automatically saves research, conversations, sources, proof of citation verification and time entries, so keeping the record is what the customer buys. Searching the vendor site, product page and third party coverage on 29 Aug 2026 found nothing on how long any of it is kept, whether customers control that, or whether deletion is available.
A product built to keep a durable record of a lawyer's work, with no published terms governing that record, leaves this gap wide open.
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 walls or matter level segregation.
Searched the vendor site, the deep research product page and third party coverage on 29 Aug 2026. No vendor material addresses segregation of any kind: not between customers, not between users, not between matters. No document management integration was located whose permissions the product could inherit. Noted for context: published customer accounts describe very small firms of two attorneys plus support staff, where formal ethical walls are less commonly operated than at scale, though conflicts obligations apply regardless of firm size.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
No located term or policy addresses third party requests for customer data.
Searched the vendor site, the deep research product page and third party coverage on 29 Aug 2026, and ran targeted searches for published terms or a privacy policy without reaching one. No clause committing to notify a customer of a government or law enforcement request for their data was located, and no transparency report was located. The gap matters because the product durably stores research, conversations and sources tied to a lawyer's matters.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
Coverage is described by jurisdiction with no identification of the underlying corpus.
Coverage is stated by jurisdiction level, without identifying sources. The vendor says the product synthesizes federal, state and local US doctrine using models grounded in US law for particular practices and jurisdictions, and the evaluator confirms broad federal and state coverage on its test set. Searched the vendor site, product page and third party coverage on 29 Aug 2026 and found no named source or publisher for primary law, no license or public domain basis, no completeness statement per jurisdiction, and no update schedule or lag. Local doctrine is claimed without saying which localities, a significant undefined boundary for a research product.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
No located public material addresses whether authority is checked for subsequent history.
A verification mechanism is published and what it verifies is not defined. The vendor puts structured citation verification at the center of its positioning and states that proof of citation verification is saved automatically with each research record, and the independent evaluator scored it highest of all participants on authoritativeness at 77 percent, defined as citing relevant primary sources that are valid and support the statements made.
Searched the vendor site, the product page and third party coverage on 29 Aug 2026 and located nothing stating whether verification checks that authority exists and supports the proposition, or whether it also checks subsequent history and treatment. Those are different questions and no commercial citator license was located. The good law question specifically is unanswered.
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.
Searched the vendor site, the deep research product page and third party coverage on 29 Aug 2026. No published material describes what the product does when it cannot ground an answer, and no explicit no answer path or confidence signal exposed to the user was located. The independent evaluator recorded four cases where the product returned nothing due to technical timeouts, which is a failure mode rather than principled abstention, and unlike one other participant in the same study no instances were recorded of it explaining that sources did not support an answer.
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 addressing fabricated or hallucinated legal citations produced by this product has been located as of the date shown. This is a statement about the public record on that one subject, not a finding about the product, and this signal is not a litigation history.
No court order, opinion or disciplinary record naming this product has been located as of 29 Aug 2026. Instrument searched: the AI Hallucination Cases database maintained by Damien Charlotin, which tracks court decisions worldwide involving AI generated hallucinated content and records the AI tool implicated where it is known. Also checked published 2026 sanctions summaries and secondary sanctions trackers. The entries located name filers, and in some rows other products, rather than this one.
This is a statement about the public record on the date shown and not a clearance. The exposure is direct: a US litigation research product produces authority bound for filings, and this vendor's independently measured authoritativeness score was the highest in its study.
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.
Searched the vendor site, deep research product page and third party coverage on 29 Aug 2026. No engagement with any ethics opinion or professional guidance was found, including ABA Formal Opinion 512 and state bar guidance. The vendor limits access to US licensed attorneys and verifies licensure at signup, a real position on who may use the tool, covered under professional responsibility, but that is not engagement with published guidance.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
A usable record of AI assisted work exists with no published fee guidance.
The product keeps a record of AI assisted work. It automatically saves time entries alongside research, conversations, sources and proof of citation verification, a per matter record the firm can use, so a firm asked what was done and how long it took has something to produce. The vendor publishes no guidance on treating that record for fees or client disclosure: searched the vendor site, product page and third party coverage on 29 Aug 2026 and found nothing on billing, no position on whether AI assisted time is billable, and no client disclosure material. The record exists; the guidance does not.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
No located public material supports a client side disclosure obligation.
Searched the vendor site, the deep research product page and third party coverage on 29 Aug 2026, and ran targeted searches for a trust center, security page or certification listing without reaching one. No subprocessor list, no statement naming which model providers see client content, no published data processing agreement, no certification and no client facing consent or notification material was located. A firm bound by a client AI clause could not assemble a response from this vendor's published material, notwithstanding that the vendor's own models being proprietary would simplify the answer if it were stated.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
Some elements of the record are available, short of a document level export.
A strong disclosure trail exists, short of identifying the model. The product automatically saves research, conversations, sources and proof of citation verification, so a lawyer facing a court's AI disclosure order has a kept record of what was asked, retrieved and cited and that citations were checked, created in normal use rather than assembled afterward. No export packaging that record as a single document was found, and no model is named anywhere, so the model used could not be stated. Litigation research output is among the most likely to attract such an order.