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Casetext website screenshot

Casetext

Casetext is a legal technology company founded in 2013 by Jake Heller, Joanna Huey, and Laurence Pfeffer and headquartered in San Francisco, California. The company built one of the earliest neural-search engines for U.S. case law (Parallel Search) and a broader research platform covering federal and state cases, statutes, regulations, and secondary sources, with citator signals delivered through its SmartCite feature. Casetext is best known for CoCounsel, a generative-AI legal assistant released in March 2023 and originally built on top of OpenAI's GPT-4, that automates document review, deposition preparation, contract analysis, legal research memos, and database queries for law firms and in-house legal teams. Companion products include AllSearch, a private document search tool that lets firms run Parallel Search across their own document collections, and Compose, an automated brief-drafting product. Thomson Reuters acquired Casetext in June 2023 for $650 million in an all-cash deal that closed in August 2023, and CoCounsel has since been integrated across Thomson Reuters' Westlaw, Practical Law, and HighQ product lines as the company's flagship legal-AI assistant. The Casetext platform is sold as a SaaS subscription to law firms, corporate legal departments, and government agencies; there is no public developer API, SDK, or open-source release, and the casetext GitHub organization contains only archived research forks (transformers, ELECTRA, pgvector, FiD) plus a handful of internal infrastructure repos that were archived after the Thomson Reuters acquisition.

human only

Index entry only — little beyond a description and a link, and nothing machine-readable enough for an agent to act on without a human reading the site first.

Kin Score

API Evangelist profiles Casetext the way a machine reads it — 2 machine-readable artifacts, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.

Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Casetext scores 12.6/100 (minimal), with a separate agent-readiness read of 0/100 (human only). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.

Kin Score

This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.

Kin Score Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 12.6/100 · minimal
Contract Quality 0.0 / 25
Developer Ergonomics 0.4 / 20
Commercial Clarity 4.7 / 20
Operational Transparency 0.7 / 13
Governance 0.0 / 12
Discoverability 6.8 / 10
Agent readiness — 0/100 · human only
Machine-Readable Contract 0 / 18
Agentic Access Contract 0 / 15
MCP Server 0 / 12
Machine-Readable Auth 0 / 10
Idempotency 0 / 9
Stable Error Semantics 0 / 8
Request/Response Examples 0 / 7
Rate-Limit Signaling 0 / 7
Typed Event Surface 0 / 6
Agent Skills 0 / 5
Well-Known Catalog 0 / 4
Consent & Bot Identity 0 / 3

How we profile Casetext

Each block below is one kind of artifact we hold for Casetext. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.

GraphQL 1

Where a provider ships GraphQL, the schema is the contract. We profile it alongside the REST surface so the whole interface is legible in one place.

GraphQL schemas published by this provider.

Casetext GraphQL Schema

This conceptual GraphQL schema models the Casetext AI legal research platform, including its core legal research capabilities, document analysis tools, and AI-powered features s...

GRAPHQL

Security Posture 1

Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Casetext Domain Security

TLSv1.3 · HSTS · DNSSEC · DMARC

SECURITY

Resources

Every other property we hold for Casetext — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.

Get Started 1

Portal, sign-up, and the first successful call

Documentation 1

Reference material describing how the API behaves

Build 1

SDKs, sample code, and the tooling you integrate with

Access & Security 1

Authentication, authorization, and security posture

Operate 1

Status, limits, changes, and where to get help

Commercial 1

Pricing, plans, and the legal terms of use

← All providers · Data indexed from github.com/api-evangelist/casetext · machine-readable index on apis.io