Invisible AI
Invisible AI is a next-generation computer vision company delivering a Vision Execution System (VES) for manufacturing. NVIDIA Jetson-powered edge devices with Intel RealSense 3D depth cameras and on-device SSD storage mount to existing factory infrastructure and, within hours, encode and segment the production floor in real time. The no-code, edge-based platform captures 100% of production cycles across every station without wearables, operator disruption, or cloud integration, then analyzes human motion and objects to surface cycle-time variability, process drift, quality escapes, and safety/ergonomics risk. Founded in 2018 by autonomous-vehicle veterans and backed by Sierra Ventures, it serves automotive and aerospace OEMs including Toyota, Ford, General Motors, BMW, Mercedes-Benz, and Nissan. Invisible AI publishes no public API or developer platform today; this profile captures its company identity, security posture, and public web surface for the API Evangelist network.
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 Invisible 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 — Invisible AI scores 14.5/100 (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 Invisible AI
Each block below is one kind of artifact we hold for Invisible 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 Invisible 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.
Build 1
SDKs, sample code, and the tooling you integrate with
Access & Security 2
Authentication, authorization, and security posture
Operate 1
Status, limits, changes, and where to get help
Commercial 2
Pricing, plans, and the legal terms of use
Company 3
The organization behind the API
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