Cognigy
Cognigy (now NiCE Cognigy, following NICE's 2024 acquisition) is an enterprise conversational and agentic AI platform for building, deploying, and operating AI Agents across voice, chat, and messaging channels. Cognigy.AI lets teams design conversational flows, connect large language models and knowledge bases, orchestrate omnichannel customer service automation, and augment human contact center agents with real-time Agent Copilot assistance. The platform exposes a comprehensive REST API (the Cognigy.AI API) for managing agents, snapshots, flows, endpoints, users, and organizations, an OData analytics endpoint, webhook and REST endpoints for real-time interactions, a Socket client for webchat, an embeddable Webchat widget, and a first-party command-line interface for managing local copies of virtual agent projects.
Limited machine-readable signal and partial portal coverage — documentation a human can read, but little a machine or agent can consume without scraping.
API Evangelist profiles Cognigy the way a machine reads it — 5 machine-readable artifacts across 1 API, 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 — Cognigy scores 40.9/100 (thin), with a separate agent-readiness read of 15/100 (agent aware). 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 Cognigy
Each block below is one kind of artifact we hold for Cognigy. 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 1
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.
Cognigy.AI API
The Cognigy.AI REST API for managing AI Agents throughout their lifecycle — deployment and snapshots, flow configuration and interaction, endpoints, resource monitoring, adminis...
Event 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.
Cognigy 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.
Resources
Every other property we hold for Cognigy — 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 5
Portal, sign-up, and the first successful call
Documentation 2
Reference material describing how the API behaves
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 3
Pagination, idempotency, versioning, errors, and events
Build 4
SDKs, sample code, and the tooling you integrate with
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
← All providers · Data indexed from github.com/api-evangelist/cognigy · machine-readable index on apis.io