Kalshi

Background

Kalshi is the first federally regulated prediction market in the United States. Traders buy and sell contracts on real-world outcomes — elections, economic indicators, weather, and more. The platform is open to everyone, but its developer API is what makes it possible for institutions, quant teams, and independent builders to integrate prediction markets into their own tools and strategies.

In a new category, documentation isn't just a support resource. It's the first thing a developer encounters when deciding whether to build on your platform. For Kalshi, every API integration that gets off the ground is a new source of liquidity, engagement, and adoption. Their growth depends on the documentation.

When a channel is a growth lever, it's important to know the audience. The people querying Kalshi's API aren't only human developers — they're also the trading bots, automated strategies, and AI agents those developers ship. When agents act on your docs, accuracy and structure matter at a different scale.

What Kalshi built

Kalshi's Mintlify deployment at docs.kalshi.com covers their full API surface for the trading platform:

• Interactive API playground — developers can test trade submissions and market queries directly in the docs, without leaving to set up a separate client
• AI assistant — keeps developers in a self-serve flow instead of opening a support ticket when they have questions
• Changelog — API changes are surfaced alongside the reference docs, so developers can stay ahead of breaking changes without context-switching to a separate status page
• OpenAPI-driven reference — spec-based generation keeps the reference accurate as the API evolves, with CI/CD keeping docs in sync with releases

Why Mintlify

Kalshi's API docs are a direct lever on developer adoption for the platform. The decision to use Mintlify came down to what a developer experiences the moment they land on the docs:

• The playground removes friction — instead of having to configure Postman or write a test script before seeing a response, a developer can try a live market query in seconds. That changes whether they keep reading or bounce.
• The AI assistant changes the support equation — when a developer gets stuck, the assistant keeps them unblocked without opening a ticket. Self-serve resolution at the docs layer reduces load on the engineering team.
• Changelog + versioning lets releases stay clean — Kalshi actively manages API versioning and breaking changes. Surfacing changelogs alongside the reference means developers don't miss changes that would break their integrations.
• Spec-based generation keeps things accurate — as a fast-moving API platform, manual doc updates don't scale. Mintlify's automated generation from the OpenAPI spec means the docs stay in sync with what's actually live.

What's next

Kalshi's team has been actively exploring how to push their docs farther:

• RSS feed for changelogs — so developers and integrators can subscribe to API changes without checking the docs manually
• Docs-synced releases — shipping changelog entries and new docs at exactly the same moment a breaking change goes live, not after

API docs are a direct lever on developer adoption. The playground alone changes whether a developer builds on Kalshi or moves on.

Brian Ta, Founding Growth Product Lead, Kalshi