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.

Cognigy is listed with 1 API on the APIs.io network. Tagged areas include Company, Conversational AI, AI Agents, Contact Center, and Customer Service Automation.

The Cognigy catalog on APIs.io includes 1 event-driven AsyncAPI specification.

Cognigy’s developer surface includes documentation, API reference, getting-started guide, support, engineering blog, signup flow, changelog, and 19 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

46.3/100 developing ▬ flat Agent 23/100 agent aware Front door AI 6/6 dominant saas Full breakdown ↓
scored 2026-10-31 · rubric v0.25.0 · Show this score on your site →

1 API 1 MCP Servers

Company Conversational AI AI Agents Contact CenterCustomer Service AutomationChatbots Voice AI Virtual Agents Enterprise AI Omnichannel

Kin Score

Kin Score How this is scored →
scored 2026-10-31 · rubric v0.25.0

Composite quality — 46.3/100 · developing

Contract Quality 8.3 / 21

Developer Ergonomics 13.4 / 17

Access Clarity 6.7 / 17

Operational Transparency 3.2 / 11

Contract Governance 1.9 / 10

Discoverability 5.6 / 9

Regulatory Posture 3.1 / 15

Agent readiness — 23/100 · agent aware

Machine-Readable Contract 18 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 12 / 12

Machine-Readable Auth 10 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 0 / 7

Typed Event Surface 6 / 6

Agent Skills 0 / 5

Well-Known Catalog 0 / 4

Consent & Bot Identity 0 / 3

A2A Agent Card 0 / 8

Dry-Run / Simulate Mode 0 / 4

Delegated User Identity 0 / 6

Protected Resource Metadata 0 / 5

Registration Without a Human 0 / 6

Agentic Commerce Well-Known Document 0 / 5

Pagination 5 / 5

Distinct Operations 3 / 3

Regulatory Posture applies to this provider. Its tags matched the AI & Biometrics regime, so Regulatory Posture carries 15 points of the composite. If this regime is wrong for your business, say so on your provider repo — the applicability map is public and we will correct it.

Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero: never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and several others — scorable at all.

The six quality facets above are damped to 85 points between them, because the conditional facet above carries the other 15. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 85% of its nominal weight, not 100%. The full arithmetic is at apis.io/rating/.

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Agent readiness — checks not met, largest first (exact, from this profile):

Agentic Access Contract +10 pts — agentic_access artifact present (x-agentic-access), graded by author
Idempotency +9 pts — OpenAPI mutating operations declare an idempotency key — a header, a request-body property, or a named de-duplication token whose own description says so (verified); else common[].type matches /idempoten/i (documented)
A2A Agent Card +8 pts — a2a/-a2a.yml manifest, graded on conformance.grade against A2A 1.0.0
Stable Error Semantics +8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes
Rate-Limit Signaling +7 pts — OpenAPI responses document X-RateLimit-* / RateLimit headers (verified), else a rate_limits artifact or RateLimits link (documented)
Request/Response Examples +7 pts — share of operations carrying request/response examples; else an Examples / Code Samples link

9 more unmet checks in the Agent Readiness table above.

Kin Score — facets with the most composite points still available (weight × headroom):

Contract Quality scores 39.0 — up to +15.3 composite points
Access Clarity scores 39.5 — up to +12.1 composite points
Contract Governance scores 18.2 — up to +9.8 composite points

Each check links to what satisfies it. Publish the artifact, or tell us where it already lives, and the score moves on the next scoring run.

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. This rating is computed from the provider profile at artifacts.apis.io/cognigy/apis.yml: open an issue on github.com/api-evangelist/cognigy to ask a question or point us at an artifact you publish. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

Markets this provider is in provisional

The Kin Score Market layer reads a provider inside its market: its position, and how deep its integrations go. Depth is only comparable within a position. Provisional and unweighted: not part of the Kin Score or agent readiness.

Market	Position	Depth	Registered MCP server	Declares compatibility
Customer Support, Helpdesk and Contact Center	standard	34.5	-	-

Registered MCP server and declares compatibility are report only — not weighted. Undeclared means we found nothing we can read, so there is no number: we never infer integrations.

APIs 1

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...

MCP Servers 1

Model Context Protocol servers that expose these APIs to AI agents.

Cognigy MCP Server

Remote MCP server at docs.cognigy.com over HTTP; 3 tools listed.

MCP SERVER

Event Specifications 1

AsyncAPI definitions for this provider's event-driven and streaming APIs.

Cognigy Webhooks

ASYNCAPI

Security Posture 3

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Cognigy Authentication

apiKey · 3 schemes

SECURITY

Cognigy Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Cognigy Trust Center

SOC 2, ISO 27001

SECURITY

Resources

Get Started 5

Portal, sign-up, and the first successful call

DeveloperPortal

DeveloperPortal

GettingStarted

GettingStarted

SignUp

SignUp

Login

Sandbox

Sandbox

Documentation 2

Reference material describing how the API behaves

Documentation

Documentation

APIReference

APIReference

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

LLMsTxt

LLMsTxt

Design & Contract 3

Pagination, idempotency, versioning, errors, and events

Components

Components

Conventions

Conventions

Webhooks

Webhooks

Build 4

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

Packages

SDKs

CLI

Access & Security 4

Authentication, authorization, and security posture

TrustCenter

DomainSecurity

Compliance

Authentication

Operate 3

Status, limits, changes, and where to get help

Support

Support

ChangeLog

ChangeLog

ChangeLog

ChangeLog

Commercial 1

Pricing, plans, and the legal terms of use

PrivacyPolicy

PrivacyPolicy

Company 3

The organization behind the API

BlogRSS

BlogRSS

Website

Website

Blog

Blog

Source (apis.yml)

aid: cognigy
name: Cognigy
description: 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.
url: https://raw.githubusercontent.com/api-evangelist/cognigy/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- insight-partners
x-tier: profiled
x-tier-reason: enriched-from-provider-surface
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: false
  label: Hosted service · you call their endpoint
  confidence: medium
  source:
  - pricing
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source:
  - authentication
  - security
  - sandbox
  generated: '2026-09-03'
  method: derived
image: https://www.cognigy.com/favicon.ico
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-10-06'
x-docs-platform: mintlify
x-docs-platform-confidence: medium
x-docs-platform-checked: 2026-09-24
tags:
- Company
- Conversational AI
- AI Agents
- Contact Center
- Customer Service Automation
- Chatbots
- Voice AI
- Virtual Agents
- Enterprise AI
- Omnichannel
tags_raw:
- Company
- Conversational AI
- Agentic AI
- Contact Center
- Customer Service Automation
- Chatbots
- Voice AI
- Virtual Agents
- Enterprise AI
- Omnichannel
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
apis:
- name: Cognigy.AI API
  description: The Cognigy.AI REST API for managing AI Agents throughout their lifecycle — deployment and snapshots, flow
    configuration and interaction, endpoints, resource monitoring, administration and user management, API key and token creation,
    debugging and logs, and the simulator. Any action available in the Cognigy.AI frontend can be queried or triggered through
    this API. Authentication is via an API key passed as an X-API-Key header or an api_key query parameter.
  humanURL: https://docs.cognigy.com/api-reference/
  baseURL: https://api-app.cognigy.ai
  tags:
  - Conversational AI
  - Management API
  - AI Agents
  properties:
  - type: Documentation
    url: https://docs.cognigy.com/api-reference/
  - type: Authentication
    url: authentication/cognigy-authentication.yml
  - type: Webhooks
    url: asyncapi/cognigy-webhooks.yml
  - type: Conventions
    url: conventions/cognigy-conventions.yml
common:
- url: https://www.cognigy.com/blog/rss.xml
  type: BlogRSS
- type: TrustCenter
  url: security/cognigy-trust-center.yml
- type: DomainSecurity
  url: security/cognigy-domain-security.yml
- type: Website
  url: https://www.cognigy.com/
- type: DeveloperPortal
  url: https://docs.cognigy.com/
- type: Documentation
  url: https://docs.cognigy.com/
- type: APIReference
  url: https://docs.cognigy.com/api-reference/
- type: GettingStarted
  url: https://docs.cognigy.com/ai/for-developers/developers/api-and-cli/
- type: Support
  url: https://support.cognigy.com/hc/en-us
- type: Blog
  url: https://www.cognigy.com/blog
- type: GitHubOrganization
  url: https://github.com/Cognigy
- type: SignUp
  url: https://www.cognigy.com/get-demo
- type: Login
  url: https://app.cognigy.ai/
- type: PrivacyPolicy
  url: https://www.cognigy.com/privacy-policy
- type: ChangeLog
  url: https://docs.cognigy.com/release-notes/
- type: Compliance
  url: https://trust.cognigy.com/
- type: Packages
  url: packages/cognigy-packages.yml
- type: SDKs
  url: packages/cognigy-packages.yml
- type: CLI
  url: cli/cognigy-cli.yml
- type: Components
  url: components/cognigy-components.yml
- type: Authentication
  url: authentication/cognigy-authentication.yml
- type: Conventions
  url: conventions/cognigy-conventions.yml
- type: Webhooks
  url: asyncapi/cognigy-webhooks.yml
- type: ChangeLog
  url: changelog/cognigy-changelog.yml
- type: LLMsTxt
  url: llms/cognigy-llms.txt
- type: Sandbox
  url: sandbox/cognigy-sandbox.yml
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence

Cognigy API — frequently asked questions

Does Cognigy have an API?

Yes. APIs.io lists 1 API from Cognigy, including Cognigy.AI API.

How do I authenticate with the Cognigy API?

Cognigy uses bearer-token authentication (apiKey · 3 schemes). The details are profiled on APIs.io as Cognigy Authentication.

Does Cognigy have an MCP server?

Yes. APIs.io lists 1 MCP server for Cognigy: Remote MCP server at docs.cognigy.com over HTTP; 3 tools listed.

Is the Cognigy API ready for AI agents?

Cognigy has a Kin Score of 46.3 out of 100 (developing) and an Agent Readiness score of 23.2 (agent-aware), scored by API Evangelist on 2026-10-31.

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