Fetcherr
Fetcherr is an Israel-based AI technology company (founded 2019, Netanya) building generative-AI decision systems for the aviation industry. Its core is the Large Market Model (LMM), a generative model trained on internal airline data plus external signals (competitor prices, demand, weather, events, economic indicators) to forecast markets and drive real-time business decisions. Fetcherr productizes the LMM as a Generative Pricing Engine (GPE) for dynamic airline pricing and as ALPHA, a cloud-based retailing and inventory-management platform that integrates with existing airline PSS and legacy infrastructure. Customers include Delta, Virgin Atlantic, WestJet, Azul, and Viva Aerobus. Fetcherr is an enterprise B2B vendor and does not publish a public developer portal, API documentation, SDKs, or self-serve credentials; integration is delivered directly to airline customers. Added to the API Evangelist network as a battery-ventures portfolio company.
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 Fetcherr 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 — Fetcherr scores 12.1/100 (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 Fetcherr
Each block below is one kind of artifact we hold for Fetcherr. 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 Fetcherr — 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
Commercial 2
Pricing, plans, and the legal terms of use
Company 2
The organization behind the API
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