Resistant AI
Resistant AI protects financial-services organizations from fraud and financial crime with AI. Its Documents product detects fake, tampered, forged, and AI-generated documents (PDFs and images) in seconds, and its Transactions product layers 80+ AI models over existing transaction-monitoring systems for AML and fraud detection. The Resistant Documents API provides programmatic document forensics — fraud, quality, classification, content extraction, and Adaptive Decision — through an OAuth2 create/upload/poll workflow across regional cells, with polling, Amazon SQS, and Svix webhook result delivery, plus a Tenant Management API for provisioning tenants and applications.
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 Resistant AI the way a machine reads it — 10 machine-readable artifacts across 2 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 — Resistant AI scores 48.0/100 (developing), with a separate agent-readiness read of 82/100 (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 Resistant AI
Each block below is one kind of artifact we hold for Resistant 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.
APIs 2
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.
Resistant AI Submission API
The Submission API from Resistant AI — 10 operation(s) for submission.
Resistant AI Tenants API
The Tenants API from Resistant AI — 4 operation(s) for tenants.
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.
resistant-ai-mcp.yml
MCP SERVERRate Limits 1
Rate limits are the difference between a demo that works and a production integration that doesn't fall over. Publishing them is an operational-transparency signal — and a hard requirement for any agent that plans its own throughput.
Documented rate limits and quota policies.
Resistant Ai Rate Limits
RATE LIMITSEvent Specifications 1
Not every API is request/response. AsyncAPI describes the event-driven and streaming side — the webhooks and channels — so the asynchronous half of the interface is documented the same way the synchronous half is.
AsyncAPI definitions for this provider's event-driven and streaming APIs.
Resistant Ai Documents Webhooks
ASYNCAPISecurity 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.
Scopes 1
OAuth scopes are the vocabulary of least-privilege access. Profiling them shows exactly what an integration — or an agent acting on a user's behalf — is allowed to do.
OAuth scopes governing access to this provider's APIs.
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 Resistant 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.
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 7
Pagination, idempotency, versioning, errors, and events
Scroll within the panel for all 7 ·
Access & Security 4
Authentication, authorization, and security posture
Operate 3
Status, limits, changes, and where to get help
Commercial 1
Pricing, plans, and the legal terms of use
Company 2
The organization behind the API
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