GC AI API
GC AI ships a public External API v1 for chat completions, files, projects, playbooks and skills, with self-serve API keys and an OAuth protected MCP server. Client libraries, event callbacks and a documented sandbox are missing, and usage is metered in credits.
Frequently asked questions
GC AI scores A- on the API Report Card. GC AI ships a public External API v1 for chat completions, files, projects, playbooks and skills, with self-serve API keys and an OAuth protected MCP server. Client libraries, event callbacks and a documented sandbox are missing, and usage is metered in credits.
GC AI has a workable official integration path. Most engineering teams can build against it directly. Open API: self-serve and documented, without SDKs or webhooks
GC AI is a cloud platform that markets itself as the AI platform for in-house legal teams, pairing a legal research and drafting assistant with workflow automation.
Legal, specifically in-house legal departments and general counsel organizations rather than law firms billing hours. Teams use GC AI conversationally for legal questions grounded in company context and public court opinions, then run playbook based contract review that returns redlines and comments, largely inside Microsoft Word or Slack where the work already happens.
Sourced research names GC AI as a platform for in-house legal teams but publishes no customer counts, revenue figures or named references, so its footprint reads as an emerging entrant in a category dominated by established legal and contract vendors.
The system of record holds legal work product: uploaded files, folders and projects, contract review outputs with redlines and comments, playbooks encoding a company negotiation position, custom skills, and the chat threads where counsel reasoning is captured.
This is a recent, cloud native product rather than a legacy system.
Inference endpoints are capped at 60 requests per minute per organization and 20 per API key, and the per-organization ceiling is shared, so minting extra keys does not raise total throughput. Every inference call returns a job envelope rather than a synchronous response, so chat completions and playbook runs that outlast the inline wait window must be polled by job_id. Full sourced list under Sources below.
Common alternatives include Ironclad, Agiloft, LexisNexis, Thomson Reuters Legal Tracker, Icertis. Graded alternatives appear under "More from the report card" below.
Grades measure one thing: can a customer's engineering team get their own data out programmatically? We check six things (whether a real API exists, how access is gated, data coverage, auth quality, docs and developer experience, and stability) and roll them into a letter grade. Grades get re-verified, and they only move on evidence.