Kata.ai
Kata.ai is an Indonesian enterprise conversational-AI company that builds AI agents and chatbots for customer experience, marketing, sales, and HR across financial services, retail, healthcare, automotive, and government. Its developer-facing Kata Platform lets teams create bot projects that bundle a Bot, CMS, and a Natural Language Understanding (NLU) model, then deploy them and connect messaging channels such as LINE, Telegram, WhatsApp, Facebook Messenger, Slack, and Qiscus. Kata.ai exposes a public REST API for managing projects, bots, deployments, environments, channels, teams, and NLUs, an NL Prediction API for entity extraction from a trained model, the kata command line tool, and the Aksara design system. Backed by 500 Global.
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 Kata.ai the way a machine reads it — 14 machine-readable artifacts across 9 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 — Kata.ai scores 40.7/100 (thin), with a separate agent-readiness read of 51/100 (agent ready). 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 Kata.ai
Each block below is one kind of artifact we hold for Kata.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 9
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.
Kata.ai Auth API
Login and token issuance.
Kata.ai Bots API
Bot revisions and drafts.
Kata.ai Channels API
Messaging channels (LINE, Telegram, WhatsApp, etc.).
Kata.ai Deployments API
Deployment versions of a project bot.
Kata.ai Environments API
Named environments binding a deployment version.
Kata.ai NLU API
Natural Language Understanding models.
Kata.ai Prediction API
Run entity prediction against a deployed NLU model.
Kata.ai Projects API
A project bundles one Bot, CMS, and/or NLU.
Kata.ai Teams API
Teams and membership.
Scroll within the panel for all 9 ·
Arazzo Workflows 2
Real integrations are rarely a single call. Arazzo describes the multi-step sequences — auth, then create, then confirm — so both a human and an agent can follow the choreography, not just the endpoints.
Multi-step API workflows described with the Arazzo specification.
_Index
ARAZZOBuild and deploy a Kata.ai bot
Log in, create a project, push a bot revision, cut a deployment version, and bind an environment.
ARAZZOMCP 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.
kataai-mcp.yml
MCP SERVERSecurity Posture 2
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 Kata.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 2
Portal, sign-up, and the first successful call
Documentation 4
Reference material describing how the API behaves
Agent Surfaces 3
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 7
Pagination, idempotency, versioning, errors, and events
Scroll within the panel for all 7 ·
Build 3
SDKs, sample code, and the tooling you integrate with
Access & Security 2
Authentication, authorization, and security posture
Operate 1
Status, limits, changes, and where to get help
Commercial 1
Pricing, plans, and the legal terms of use
Company 1
The organization behind the API
Other 1
Properties that don't map to a standard resource type
← All providers · Data indexed from github.com/api-evangelist/kataai · machine-readable index on apis.io