CBRP Co.
The Judgment Layer

CBRP Co.

The Judgment Layer for Legal Professionals.

$12B+ has been invested in legal technology. Nearly all of it makes work faster.
We built a platform that makes legal teams think sharper.

$1–$1.25M Seed  ·  cbrp.ai

Confidential — This document is being furnished to a limited number of prospective investors on a confidential basis for informational purposes only. It does not constitute an offer to sell or a solicitation of an offer to buy any securities. Any such offer or solicitation will be made only pursuant to definitive agreements and other documents provided to qualified investors. The information herein is preliminary, provided for discussion purposes only, and may not be relied upon as an indication of future results. Certain statements are forward-looking and involve risks and uncertainties. Actual results may differ materially. No representation or warranty is made as to the accuracy or completeness of this information. © 2026 CBRP Co. All rights reserved.
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Legal Teams Make Thousands of Judgment Calls a Year.
Nothing in Their Tech Stack Helps Them Make Better Ones.


Intelligence Is Generic

Law firm alerts are written for everyone. A GC at a PE-backed logistics company and a GC at a public biotech get the same briefing. The work of figuring out what actually matters to your company falls entirely on you.

Teams Think in Silos

The GC sees risk through a legal lens. The VP of Operations sees it through an operational lens. Nobody sees where those perspectives diverge. The most dangerous exposures live in the gaps between how different functions perceive the same event.

Judgment Develops by Accident

Pilots have flight simulators. Surgeons have cadaver labs. Legal professionals develop judgment through years of unstructured experience with no feedback loop. Whether you get good depends on what cases you happen to see and who happens to mentor you.

$12B+ is spent annually on legal technology. Nearly all of it makes work faster. None of it makes thinking sharper.

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What We Built

The judgment layer
for legal professionals.

CBRP delivers intelligence that learns your company, shows you what your team actually thinks, and develops sharper judgment over time. Five products, one engine.

CounselBrief

Personalized legal intelligence for in-house counsel.

CB Analytics

Anonymized GC demand intelligence for law firms.

CB Acuity

The flight simulator for legal judgment.

DirectorBrief

Board intelligence for individual directors.

RegulatorPulse

Compliance intelligence for small businesses.

One engine. Five products. Each one deepens the advantage.

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AI-Driven Change Is Coming to Law Faster Than Legal Teams Can Adapt.


AI will reshape the practice of law, that much is certain. The tools in the current wave of AI disruption drive process efficiency and speed. None of them help legal professionals think better in a world that's changing faster than any individual can track.

Other Professions Have Simulators. Law Doesn't.

Jayden Daniels broke the NFL rookie completion record by using VR to simulate thousands of defensive reads before he ever took a snap. Pilots train in flight simulators. Surgeons practice on cadaver labs.

Legal professionals develop judgment through years of unstructured experience with no feedback loop. The profession that makes the highest-stakes decisions in the most complex environment has the least structured way to develop the skill that matters most: judgment.

"AI cannot replace high-level human judgment. The ability to interpret AI-generated insights and make strategic, high-stakes decisions remains a purely human domain."

Jamie Dimon

CEO, JPMorgan Chase

"Build systems that treat AI as a cognitive amplifier — a tool to reliably extend human thinking."

"2026 will be a pivotal year for AI. We have moved past the initial phase of discovery and are entering a phase of widespread diffusion."

Satya Nadella

CEO, Microsoft · January 2026

CBRP enables legal teams to adapt and scale with AI-driven change, whatever form it takes.
Not by automating their work, but by sharpening the human judgment that no automation can replace.

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The Market Built a Process Layer.
Nobody Built the Judgment Layer.


The Process Layer

Harvey Contract execution and AI-assisted drafting
Legora Document review, research, drafting workflows. $5.5B valuation, 800+ firms. Zero judgment infrastructure.
GC AI Document interaction and retrieval
Spellbook Word-native contract drafting and review. 4,000+ teams.
CoCounsel Legal research workflows (Thomson Reuters/Westlaw)
Lexis+ AI AI research layer on LexisNexis. Incumbent play.
Ironclad Contract lifecycle management
Diligent Board materials and governance process

Billions invested. All execution. None of it helps a legal team make better judgment calls.

The Judgment Layer

Proactive Surfaces what matters before you ask
Role-aware Same regulation, different framing for different roles
Contextual Knows your companies, committees, jurisdiction
Networked Cross-functional risk sensing: legal and business score the same events
Calibrated Closed-loop feedback: outcome detection shows whether the call was right
Compounding Every interaction trains the model. The product sharpens with use.
Training Actively develops judgment via micro-learning tools

This layer didn't exist. We built it.

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Five Products. One Engine.


CounselBrief

Personalized legal intelligence for in-house counsel. Company-specific context turns generic news into specific briefings. Every scored interaction builds a portable Judgment Profile. At the enterprise tier, the GC orchestrates: business unit leaders score alerts through their operational lens, and divergences reveal where legal and business see risk differently. 100K+ US GCs.

CB Analytics

CB ACUITY LAW FIRM COMPANION

The other side of the CounselBrief data asset. Anonymized GC demand intelligence sold to law firms as a BD tool. Which practice areas are surging? Where is judgment diverging from market consensus? Law firms buy visibility into the demand signal their clients generate. They also feed their memos through the platform, reaching GCs engaging with those exact topics. Bidirectional marketplace.

CB Acuity

The flight simulator for legal judgment. Three channels:

  • Enterprise: Bundled with CB Enterprise.
  • Law firms: $15-25K/yr, associate training.
  • Law schools: $5-10K/yr, ABA practice-readiness.

Every law student trained on Acuity becomes a future GC who already knows the platform.

DirectorBrief

Board intelligence for individual directors. Nobody serves them: Diligent sells to the corporate secretary, AlphaSense costs $10K+/seat, NACD is education only. Committee-contextualized alerts. D&O severity up 27% to $56M avg settlement. 250K+ US board seats.

RegulatorPulse

Same engine, calibrated for a non-legal audience. 33M+ US small businesses, 77% relying on Google for regulatory guidance. Translates complexity into actionable guidance without a lawyer. A product trained on Wall Street, walked down to Main Street.

One engine. Five products. Each one deepens the advantage.

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Five Distinct Buyer Pools. One Engine Serves All Five.


In-House Counsel

100K+
US General Counsel & Deputy GCs

CounselBrief Individual + enterprise plans

Source: ACC, CLOC

Law Firms + Law Schools

450K+
US associates + 35K 3L students/yr

CB Acuity Judgment training for associates, partners, and law students

Source: NALP, AmLaw, ABA 509

Law Firm BD + Strategy

AmLaw 200
Practice group leaders + marketing

CB Analytics Anonymized GC demand intelligence + targeted memo distribution

Source: AmLaw, NLJ 500

Board Directors

250K+
US board seats (public & private)

DirectorBrief Individual + enterprise plans

Source: BoardEx, NACD, PitchBook

Regulated Small Business

33M+
US small businesses

RegulatorPulse Individual + SMB plans

Source: SBA, U.S. Chamber

Five buyer pools. Five products. The same engine — with a different persona — serves each one.

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Every Interaction Generates Judgment Data. It Compounds.


What Every User Generates

  • Judgment scores - Material / Monitor / Not Material across 15 practice areas
  • Decision lineage - from presentation to vote to action to outcome
  • Smart Dismiss reasons - "We have no outstanding debt" is richer than "Doesn't Matter"
  • Score corrections - a GC who changed from Not Material to Material is telling us something
  • Calibration data - was the GC right? Outcome detection closes the loop

Every subscriber interaction is both product delivery and a training sample. The judgment scores users generate are the reinforcement data for our proprietary model.

What we don't collect: AI conversation content. Ever. Company-specific data stays siloed per account. Judgment patterns train the base model for everyone. This is architecture, not policy.

What It Becomes: Four Levels of Intelligence

Level 1: Direct Signal

GC scored IP assignment as "Material" 12 times. The system prioritizes IP alerts. Any preference form could capture this. Necessary but not sufficient.

Level 2: Adjacent Inference

GC never scored derivative works, but their IP assignment, trade secret, and open source scores triangulate around it. The system infers a priority the GC hasn't articulated. No preference form captures this.

Level 3: Closed-Loop Calibration

GC dismissed an antitrust signal in March. The DOJ opened an investigation in April. The system detects the outcome and adjusts future relevance weights. The system and the human improve together.

Level 4: Network Intelligence

When 30 PE-backed GCs flag the same FTC enforcement pattern, the 31st sees it proactively. Individual judgment compounds into collective intelligence.

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Why This Data Matters

An ant colony runs on 10 to 20 chemical signals.
The behavioral data they produce — and the colony-level intelligence that emerges — is orders of magnitude richer.

"Ant colonies work through a network of very simple local interactions.
Individual ants use their recent experience to decide what to do.
The whole colony operates through a network of these very brief interactions."

— Deborah Gordon, Stanford University

STRUCTURED SIGNALS

Relational. Discrete. Explicit.

Judgment scores across 15 areas

Smart Dismiss reasons

Company intelligence profiles

Vote signals & corrections

Acuity drill performance

What users tell us.

EMERGENT INTELLIGENCE

No single user creates this.

What the profession cares about right now

Where judgment is weakening across roles

Judgment profile archetypes by industry

Market-level regulatory attention signals

Predictive patterns no survey captures

What the colony knows.

BEHAVIORAL SIGNALS

Vector. Continuous. Implicit.

Dwell time & engagement depth

Navigation path signatures

Topic combination patterns

Cross-user attention convergence

Temporal priority shifts

What users reveal without knowing it.

Through isolated interactions, each ant produces macro intelligence.
Similarly, each user's interaction with our tools produces valuable macro data that compounds with every user who joins.

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Others Handle Process. CBRP Develops Judgment.


The Node Model

Each user's company becomes an intelligence node. At signup, we build a structured profile: what they do, where they operate, what regulations apply. Every alert is evaluated against this model. "This EPA amendment impacts your polymer coatings product line," not "this may affect manufacturing." Cold start drops from months to weeks.

The Macro Model

Across all users, attention patterns reveal what's emerging before it's news. When 30 fintech GCs shift focus to state money transmission licensing, the 31st sees it proactively. Cross-role correlation multiplies: GC + director at same company engaging the same development = confirmation signal neither produces alone.

Both models train from passive signals — dwell time, clicks, scroll depth. No chat logs. No surveys. Users engage with their briefing and the system learns.

Others handle process.
CBRP develops judgment.

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This Is Not a Newsletter. It Is an Intelligence System.


Enterprise subscribers don't just receive intelligence. They operate inside a system that learns their company, connects their team, and gets sharper every day.

Signal Intelligence

The GC invites business unit leaders as Signal Correspondents. Each scores curated alerts through their operational lens. The GC gets aggregated risk visibility across the entire organization. The real intelligence is in the divergences: when Legal scores "Not Material" but Operations scores "Material," that gap is where hidden exposure lives.

Living Company Dossier

Continuously updated intelligence file: acquisitions, litigation, exec changes, risk factors, regulatory filings. Every alert is contextualized against what the company is actually facing today, not a static profile set during onboarding.

PE Portfolio Intelligence

Cross-portfolio alerting for PE firms. When one portfolio company faces a regulatory action, every sibling GC is briefed simultaneously. The institutional memory no org chart captures.

A Day in the Life: Enterprise GC

6:30 AM

Personalized daily brief arrives. 8 alerts ranked by company relevance, each with specific practice points and action items grounded in the living dossier.

7:15 AM

GC scores alerts: 2 Material, 3 Monitor, 3 Not Material. Dismisses one with a note: "We exited that market in Q3." System learns.

9:00 AM

System pushes a targeted update request to the VP of Operations on an OSHA development. She scores it "Material" and adds context. GC now has an operational read Legal wouldn't have surfaced alone.

2:00 PM

Sister portfolio company is implicated in a CFPB enforcement action. GC knows before the PE sponsor reaches out.

EOD

5 judgment calls recorded. 1 divergence resolved. 2 action items generated. Tomorrow's brief will be sharper because of today's decisions.

Enterprise

$30-50K/yr

Individual

$99-199/mo

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Judgment Is Trainable. No Legal Product Trains It.


Three decades of cognitive science demonstrate that professional judgment improves through structured exposure, active triage, and calibration feedback. Not passive information consumption. Every other legal product delivers information. CBRP develops the professional.

What the Research Shows

Pattern Recognition (Klein, 1998)

Experts don't compare options. They recognize patterns from accumulated exposure and act. Compressed, structured exposure accelerates this process by years.

Calibration Training (Tetlock, 2015)

People who received calibration feedback outperformed intelligence analysts with classified access. Alignment between confidence and accuracy is trainable.

Deliberate Practice (Ericsson, 2008)

Years of experience correlate weakly with actual performance. What matters is structured practice with feedback. Most professions, including law, lack this infrastructure.

Gist-Based Reasoning (Reyna, 2012)

Experts reason from gist, not verbatim detail. Better judgment comes from better gist extraction, not more information. More data often makes decisions worse.

How CounselBrief Deploys It

Active Triage, Not Passive Reading

Every alert requires a judgment: Material, Monitor, or Not Material. Each call is a micro-repetition of the core GC skill. Daily use across 14 practice areas builds pattern recognition no CLE can match.

Peer Benchmarking

"78% of GCs at PE-backed companies marked this Material." The gap between your assessment and the cohort is where judgment sharpens. No expert panel required; the network is the panel.

Calibration Feedback

"You marked this Not Material in March. The DOJ opened an investigation in April." Over time, users see their own calibration curves improve. No legal product offers this.

Gist Delivery

A 47-page SEC enforcement action becomes a contextualized brief with practice points specific to the GC's company. We deliver the gist in a micro-learning environment. Every item is searchable — the issue they saw two months ago is retrievable when they need to go deeper. An outsourced brain.

The result: CounselBrief doesn't just inform. It makes the general counsel measurably better at being a general counsel. The more they use it, the sharper they get. That's the habit loop no competitor can replicate.

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60 Years of Pattern Recognition. Now Systematized.


Steve Tyndall

CEO & Co-Founder

28 years in BigLaw. Saw firsthand how judgment is built — and how the apprenticeship model is breaking. Built all four CBRP products.

Kin Gill

Co-Founder

General Counsel and Chief Legal Officer for over 15 years, following over 15 years in BigLaw. Lives the in-house counsel workflow every day.

First hires: engineering, content, and marketing. Team stays lean.

One founder built the product because he lived the problem for 28 years. The other lives it every day as a sitting CLO.

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Five Products Live. $0 Marketing. $1–$1.25M Builds the Team and Accelerates to $3.1M ARR.


3
live products in beta
$0
marketing spend to date
24 mo
runway at raise

Traction Highlights

  • Alpha testers across multiple domains.
  • Deep company dossier engine live - PE portfolio cross-intelligence operational.
  • Signal Intelligence live - cross-functional scoring with divergence detection.
  • Automated dossier refresh and cross-portfolio alerting in production.
  • DirectorBrief: Live, demonstrating platform replicability.
  • RegulatorPulse: Live at regulatorpulse.com.

Key signal: Enterprise accounts at $40K/yr anchoring ARR from day one. Product-market pull without paid acquisition.

Year 1 Year 2 Year 3
Subscription ARR $383K $1.4M $3.1M
Enterprise ARR ($40K/yr accts) $160K $640K $1.6M
CB Ecosystem % 84% 90% 93%
Enterprise + Acuity ARR $220K $1.0M $2.4M

This raise builds the team and funds the path to profitability. A Series A becomes a choice, not a necessity.

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$1–$1.25M Seed Round

CBRP Co.  |  cbrp.ai  |  The Judgment Layer.

Milestones

12-month

168 paying CB individual subscribers, 4 enterprise contracts, 2 Acuity law firm deployments. $383K ARR. Unit economics proven.

18-month

Acuity in 5 law firms and 2 law schools. Enterprise deals accelerating. Five products live across all segments. $675K ARR run rate.

24-month

$1.4M ARR. CB Ecosystem at 90% of revenue. 12 Acuity deployments across firms and schools. Judgment data compounding. Raising Series A from a position of strength.

Use of Funds

40% — Team

$500–625K

30% — User Acquisition

$375–470K

20% — Content Engine + Model

$250–312K

10% — Operations

$125–156K

"The subscription funds the data. The data trains the model. The model sharpens the product."

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