Physical Intelligence
Physical Intelligence (often styled "Pi" or "π") is a San Francisco-based research company building general-purpose foundation models for robotics with the stated goal of producing learning algorithms that can control any robot to do any task. The company has published a continuing line of Vision-Language-Action (VLA) models: π0 (October 2024, first generalist multi-task multi-robot policy), π0-FAST (autoregressive variant via Real-time Action Chunking / FAST tokenization), π0.5 (April 2025, open-world generalization), π*0.6 (November 2025, reinforcement-learning from experience), and π0.7 (April 2026, steerable model with emergent capabilities). Physical Intelligence releases significant work as open source: the openpi repository (~12K stars) is the canonical home for π0 weights and code, with companion repos including real-time-chunking-kinetix, pi-data-sharing, aloha, augmax, and rlds_dataset_builder. The company does not yet offer a hosted commercial API; access to the platform is via open-weight models and research collaborations.
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 Physical Intelligence 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 — Physical Intelligence scores 7.9/100 (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 Physical Intelligence
Each block below is one kind of artifact we hold for Physical Intelligence. 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 Physical Intelligence — 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.
Build 1
SDKs, sample code, and the tooling you integrate with
Access & Security 1
Authentication, authorization, and security posture
Company 6
The organization behind the API
Other 2
Properties that don't map to a standard resource type
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