Fenrock AI
Fenrock AI is a Y Combinator (W26) company building specialized AI agents for the banking back office. Founded in 2026 and based in San Francisco by Charu Sharma and Michael M., Fenrock overlays on a bank's existing systems and ingests internal policies and standard operating procedures to automate compliance, financial-crime, and loan-operations workflows without requiring data migration. Its agents assist analysts with alert triage, case investigation, suspicious-activity-report (SAR) drafting, quality assurance, enhanced due diligence, KYC/KYB reviews, and sanctions/PEP monitoring, while preserving bullet-proof audit logs designed to pass regulatory examinations. Fenrock positions itself as an AI workspace that lets a single analyst process many times the volume of financial-crime and money-laundering cases. This profile is an API Evangelist network company record; Fenrock is an enterprise product company with no public API, developer portal, or documentation surface at this time.
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 Fenrock 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 — Fenrock AI scores 7.7/100 (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 Fenrock AI
Each block below is one kind of artifact we hold for Fenrock 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 Fenrock 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.
Access & Security 1
Authentication, authorization, and security posture
Company 4
The organization behind the API
Other 1
Properties that don't map to a standard resource type
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