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Paxton AI website screenshot

Paxton AI

Paxton AI is a legal AI assistant built for attorneys and law firms, delivering rapid case-law and regulatory research, AI-assisted document drafting, file analysis, deposition and discovery summarization, and specialized workflows for medical chronologies and billing summaries. Founded by Tanguy Chau (CEO) and Michael Ulin and headquartered in Bend, Oregon, the company has raised roughly $28M across a $6M seed round led by WVV Capital and a $22M Series A led by Unusual Ventures, with participation from Kyber Knight and 25Madison. Paxton's platform covers US federal regulations, state laws, and case law across all fifty states, surfaces precise authority-linked citations, and runs in a closed model environment that is SOC 2, ISO 27001, and HIPAA compliant with data never used for model training. The product is delivered as a web SaaS targeted at solo practitioners, small and mid-size firms, and enterprise legal teams across personal injury, family, employment, criminal, and corporate practice areas; commercial access is sold via per-seat Individual plans ($499/month or $2,999/year) and a volume-priced Enterprise plan, with a 7-day free trial. Paxton publishes a small public GitHub presence with citator and legal-hallucination benchmark datasets but does not offer a public developer API, SDK, or open-source platform.

human only

More than an index entry, but the surface is still mostly links rather than artifacts — the cohort most likely to move a full band from modest, well-targeted work.

Kin Score

API Evangelist profiles Paxton AI the way a machine reads it — 1 machine-readable artifact, 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 — Paxton AI scores 18.2/100 (emerging), 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 — 18.2/100 · emerging
Contract Quality 0.0 / 25
Developer Ergonomics 0.4 / 20
Commercial Clarity 8.9 / 20
Operational Transparency 2.1 / 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 Paxton AI

Each block below is one kind of artifact we hold for Paxton AI. 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.

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.

Paxton Ai Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

Every other property we hold for Paxton AI — 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 2

Portal, sign-up, and the first successful call

Build 1

SDKs, sample code, and the tooling you integrate with

Access & Security 2

Authentication, authorization, and security posture

Operate 1

Status, limits, changes, and where to get help

Commercial 3

Pricing, plans, and the legal terms of use

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