KelAI
KelAI (Kelai) is an AI quant research platform for hedge funds and institutional investors that positions itself as an autonomous alpha engine. Its AI agents run the full systematic-research workflow — generating trading-signal ideas, writing and testing research code, analyzing market data, running backtests and validation, and monitoring live signal performance — consolidating what normally runs across siloed systems and inefficient workflows. Founded by Jeremie Cohen, a former WorldQuant portfolio manager and head of event-driven systematic strategies who also led machine learning teams at Millennium Management, KelAI is part of Y Combinator's Spring 2026 batch and is deployed with institutional investors. As an early-stage company it does not yet publish a public developer API, documentation, or SDKs.
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.
API Evangelist profiles KelAI 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 — KelAI scores 7.7/100 (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
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile KelAI
Each block below is one kind of artifact we hold for KelAI. 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.
Resources
Every other property we hold for KelAI — 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.
Access & Security 1
Authentication, authorization, and security posture
Company 1
The organization behind the API
← All providers · Data indexed from github.com/api-evangelist/kelai · machine-readable index on apis.io