Tenyks
Tenyks is a University of Cambridge spin-out (Y Combinator; backed by Speedinvest) building a visual-intelligence platform for computer vision. Its original product is an MLOps monitoring and validation platform that helps ML engineers working with computer-vision data find and fix what is wrong with their models — data-quality analysis, model performance comparison, text-to-image / image-to-image / object-level similarity search, embeddings, tagging and custom metadata across image and video datasets. Tenyks has since extended into a Vision AI / Video AI Agents platform that turns everyday camera feeds into privacy-first operational analytics for brick-and-mortar businesses. The Tenyks API (currently alpha, for Premium/Dashboard users, with a freemium Sandbox) lets teams authenticate with an API key + secret to obtain a Bearer token, then create datasets and models, and upload and ingest annotations and predictions directly from AWS S3, GCS or Azure. A Python SDK and CLI wrap the same surface.
Real signal across most facets with visible, nameable gaps — the contract exists but is thin, or the portal is good while governance and commercial terms are absent.
API Evangelist profiles Tenyks the way a machine reads it — 8 machine-readable artifacts across 3 APIs, 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 — Tenyks scores 48.8/100 (developing), with a separate agent-readiness read of 69/100 (agent native). 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 Tenyks
Each block below is one kind of artifact we hold for Tenyks. 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.
APIs 3
Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.
Individual APIs this provider publishes, each with its own machine-readable definition.
Tenyks Auth API
Obtain a Bearer access token from an API key and secret.
Tenyks Data Upload API
Upload and ingest annotations, models and predictions from cloud storage.
Tenyks Datasets API
Create and retrieve datasets.
MCP Servers 1
Model Context Protocol servers expose these APIs directly to AI agents. We profile them because agent-native access is the fastest-growing way this provider's capabilities actually get used.
Model Context Protocol servers that expose these APIs to AI agents.
tenyks-mcp.yml
MCP SERVERSecurity Posture 3
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.
Agentic Access 1
An x-agentic-access contract marks which operations are safe for an agent to run on its own and which need a human in the loop. It is the difference between an API an agent can use and one it can use safely.
Recommended x-agentic-access execution contracts for AI agents.
Resources
Every other property we hold for Tenyks — 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.
Get Started 4
Portal, sign-up, and the first successful call
Documentation 2
Reference material describing how the API behaves
Agent Surfaces 5
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 5
Pagination, idempotency, versioning, errors, and events
Build 3
SDKs, sample code, and the tooling you integrate with
Access & Security 4
Authentication, authorization, and security posture
Commercial 1
Pricing, plans, and the legal terms of use
Company 2
The organization behind the API
Other 1
Properties that don't map to a standard resource type
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