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Briefly
Briefly is an AI platform for law firm marketing and business development teams, built around directory submissions to Chambers, Legal 500, IFLR, Benchmark and WTR. A firm uploads past submissions as PDF, Word or Excel files, and the AI extracts every matter, attorney, client, referee and narrative into an Experience Graph that links them across years, directories and practice areas. From that graph the team schedules and tracks open submissions across more than 5,000 practice and location cohorts.
It drafts in an in app editor by dragging matters and attorneys onto the page, converts a submission from one directory's format to another with a view of what changed, and exports to Word in each directory's format. A chat interface answers questions about the firm's matters with citations to the source records and generates pitch sections, RFP answers, partner bios and website copy. A rankings view tracks tiers and attorney rankings year over year. Briefly is made by Precedent Labs Inc. of San Francisco, states SOC 2 Type II compliance and publishes no prices.
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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.
Models do the work that replaces manual entry. They extract matters, attorneys, clients, referees and narratives from uploaded submissions into the Experience Graph and map fields when a submission moves between directories. They also answer questions about the firm's experience and draft pitch, RFP, bio and website copy from the graph. Around that sit conventional workflow tools: a deadline schedule, assignment and status tracking, section by section review, an editor with Word export and a rankings tracker. Those would still run without the models, though the graph that feeds them would have to be built by hand.
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.
Chat answers and generated content cite the matters, attorneys and past submissions they draw on, so a reader can open the record behind a claim. The product works only from the firm's own graph and general firm information. Briefly calls its output grounded and never hallucinated, but gives no accuracy figure for extraction, conversion or generated text. The website terms say AI output may not be fully accurate and that its factual assertions need independent verification.
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.
People stay in the loop at several points. Submissions move through drafting, in review and submitted, with section by section review and assigned owners. A conversion between directories shows a view of what changed and flags fields that need review, for example 92% mapped automatically with four fields left for a person. Drafts are edited in the app before export. Nothing describes a confidence level that stops the system, or what happens when an extracted matter is wrong.
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.
No customer, deployment or result is named. The figures on the site describe the problem rather than outcomes: 200 submissions a year at six partner hours each, 1,200 partner hours and 5,000 hours of marketing time, and more than $1 million lost to manual work. Survey statistics on rankings and general counsel come from a third party study, not from Briefly customers.
Privilege and Confidentiality Posture
How client confidences are handled: attorney client privilege and work product treatment, segregation of one client matter from another, whether client data trains any model, and what the vendor commits to in writing rather than in marketing.
Confidential matter narratives and client relationships are the data Briefly holds. Its security page commits that a firm's content is never used to train AI models, its own or its subprocessors', and is used solely to operate the service for that firm. Foundation models run under strict no training provisions, and sensitive operations go through dedicated infrastructure. Access runs on role based permissions, single sign on and granular access policies in isolated environments.
These commitments sit on the website rather than in a published customer agreement, and privilege, retention and deletion of firm data are not addressed.
UPL and Professional Responsibility Posture
Whether the vendor is clear that it supplies a tool rather than legal advice, who its audience is, and how it addresses unauthorized practice of law, competence and supervision duties, and jurisdiction limits. ABA Formal Opinion 512 is the reference point. Where the advice line is not the duty a product raises, the axis is read through the nearest professional duty it does raise: judicial conduct rules and the reviewing duty for products sold only to courts, and the duty to bill for time actually spent for products that draft time entries.
Section 3.2 of the website terms tells users that AI output may not be fully accurate and that its factual assertions need independent verification before reliance. The output is marketing and directory content rather than advice to clients, but submissions, pitches and website copy are still subject to professional conduct rules on lawyer advertising and client confidentiality. Those rules are not mentioned, and nothing says who in a firm may use the product.
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.
No AI policy, principles, testing method or accountable owner is published. The security page covers data handling and audits, not how extraction or generation is tested, and nothing addresses uneven results across practice areas, directories or languages.
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.
Data is encrypted with AES-256 at rest and TLS 1.3 in transit, and access runs on role based permissions, single sign on, granular policies and audit logs. Hosting uses isolated environments with automated backups and disaster recovery. Incident response procedures are documented, with notification commitments written into every contract, and penetration tests and third party audits run each year. The subprocessor list is shared only under NDA.
The privacy policy keeps personal data for as long as its purposes require, and no retention or deletion period is stated for a firm's matters, submissions or chat history.
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 only published terms govern use of the website. They warn that AI output may be inaccurate, but state no cap, indemnity, warranty or insurance for the product a firm subscribes to. The customer agreement is not published.
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.
The Experience Graph is said to be extracted from a firm's existing systems and kept current, but none of those systems is named. Documented routes in and out are file uploads of past submissions in PDF, Word or Excel, export to Word in each directory's format, and single sign on. No connection to an experience management system, CRM, document management system or the directories' own submission portals is described.
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.
Delivery is a hosted service on enterprise cloud infrastructure with isolated environments for each firm, automated backups and disaster recovery. The cloud provider, the regions used and where model calls are processed are 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.
A SOC 2 Type II audit covers security, availability, processing integrity, confidentiality and privacy and is repeated annually. The report, penetration test remediation reports, questionnaire responses and the subprocessor list go to active customers and prospects in active evaluation under NDA. The auditor and audit period are not named, and there is no open trust center.
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.
Foundation models run under strict no training provisions, with sensitive operations routed through dedicated infrastructure. The models, their providers and where they run are not named, and no notice of a change in provider is promised.
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 price, plan, unit of charge or contract term is published. Every route leads to a demo request or the sales address. The site's cost argument is about the firm's own labor, more than $1 million a year in partner and marketing time, not about what Briefly costs.
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.
The buyer is the marketing and business development team of a law firm that files many directory submissions, sized around 200 or more a year. Five directories are supported from the start, Chambers, Legal 500, IFLR, Benchmark and WTR, with more than 5,000 practice and location cohorts and a growing list of others. Every practice area those directories rank is in scope. Smaller firms, in house teams and directories outside the five are not addressed, and the jurisdictions covered beyond the directories' own lists are not stated.
2 public documents
The public pages on file for Briefly, 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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briefly.legal/security3 signals
Client Data in Training, Ethical Walls and Matter Segregation, Outside Counsel Guideline Readiness
Read Oct 13, 2026
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Fabricated Citation Record
Read Oct 13, 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 public policy or trust page states no training on customer content, with no matching term located in the published agreement.
The security page states that a firm's content is never used to train AI models, Briefly's or its subprocessors', and that foundation models run under strict no training provisions. The same promise appears in the product FAQ. The only published terms govern website use, so no matching clause in a customer agreement can be read.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
No located public material states how long prompts and outputs are retained.
How long chat prompts, generated content, uploaded submissions and the Experience Graph are kept is not stated. The privacy policy covers personal data, kept for as long as its purposes require, and backups are automated.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
Segregation is asserted in public materials with no published detail on how it is enforced.
Each firm runs in an isolated environment, and access inside it is governed by role based permissions, single sign on and granular access policies. How those policies keep one practice group's or client's matters from users who should not see them is not described.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
No located term or policy addresses third party requests for customer data.
Neither the website terms nor the privacy policy addresses requests from authorities or third parties for a firm's data, and the customer agreement is not published.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
No located public material identifies the corpus behind the product’s answers.
Answers and drafts come from the firm's own matters, attorneys, submissions and rankings, plus general firm information. No body of law is involved.
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.
The product works on a firm's matters and directory content and cites no legal authority, so there is nothing for a citator to check.
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.
Nothing describes what the chat does when the graph holds no answer. Conversions flag fields that could not be mapped automatically, which covers format mapping rather than factual uncertainty.
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.
The AI Hallucination Cases database maintained by Damien Charlotin, which records court decisions worldwide that address hallucinated AI content and the tool involved where known, has no entry naming Briefly or Precedent Labs. Briefly produces directory submissions and marketing content, not court filings.
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.
No ethics opinion or bar guidance is engaged, including the rules on lawyer advertising that govern directory and marketing content.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
The product does not touch a fee between a lawyer and a client. It operates before an engagement exists, or it is bought by a team that bills no client for the work. Savings claims aimed at the buyer’s own cost are recorded in the summary and do not make the row a savings claim, because no client bill is in the loop.
The work Briefly supports, directory submissions, pitches and marketing, is business development done before any engagement and billed to no client. Its savings claims concern the firm's own partner and marketing time, put at 1,200 partner hours and 5,000 marketing hours a year for a firm filing 200 submissions.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
The material exists behind a sales conversation or an executed agreement.
The SOC 2 report, security questionnaire responses and the subprocessor list are shared on request under NDA, to active customers and prospects in active evaluation. Nothing is published on the open site.
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 verification certification.
Output goes to legal directories and marketing channels rather than courts, and no record of AI involvement is produced.