Efference AI
Efference AI is a robotics perception and compute company building the hardware-plus-software foundation for data-driven robotics at scale. Founded in 2025 by Gianluca Bencomo and based in San Francisco (Y Combinator Fall 2025), Efference treats machine vision as a software problem, pairing affordable stereo-camera hardware with learned 3D-perception foundation models ("cheap hardware + great algorithms"). Its M1 device targets distributed, robotics-grade data collection at scale, while the H1 stereo system is built for real-time cloud inference with foundation models. The company serves autonomous vehicles, humanoid robots, and drones, and publishes hardware-interfacing documentation and firmware through its GitHub organization. As of this profile Efference exposes no public developer API, OpenAPI, or authenticated service surface.
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 Efference 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 — Efference AI scores 10.0/100 (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 Efference AI
Each block below is one kind of artifact we hold for Efference 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.
Resources
Every other property we hold for Efference 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.
Documentation 1
Reference material describing how the API behaves
Build 1
SDKs, sample code, and the tooling you integrate with
Access & Security 1
Authentication, authorization, and security posture
Operate 1
Status, limits, changes, and where to get help
Company 1
The organization behind the API
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