For Agents
Create and manage AI chatbots, run streaming chat sessions, and upload knowledge sources so agents can deliver retrieval-augmented conversations.
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Chatsistant API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
What an agent can do with Chatsistant API API.
Provision new chatbots with name, model, and persona configuration via /chatbot/create
Open chat sessions for end users and stream message responses token by token
Attach custom agents to a chatbot for tool-calling and specialised behaviour
Upload file data sources so chatbots ground answers in domain knowledge
GET STARTED
Use for: I need to create a new AI chatbot for my product, Start a chat session for an end user with a specific chatbot, Stream a chatbot response message back to my frontend, Upload a knowledge file so the chatbot can answer from it
Not supported: Does not handle telephony, SMS messaging, or human agent ticketing — use for managing AI chatbots, sessions, and knowledge sources only.
Jentic publishes the only available OpenAPI document for Chatsistant API, keeping it validated and agent-ready.
Jentic publishes the only available OpenAPI specification for Chatsistant API, keeping it validated and agent-ready. Chatsistant lets you build, deploy, and operate AI chatbots that combine conversational sessions, custom agents, and uploaded knowledge sources. Through its API you can spin up a new chatbot, create chat sessions for end users, stream responses back to clients, and attach file-based data sources for retrieval-augmented answers. It is designed for teams embedding domain-specific assistants into web apps, customer support flows, or internal knowledge tools.
List, fetch, update, and remove chatbots from a workspace
Drive end-to-end chatbot lifecycle from creation to retirement through one API
Patterns agents use Chatsistant API API for, with concrete tasks.
★ Embedded Support Chatbot
Build a customer support chatbot that answers questions grounded in your help center documentation. Create the chatbot via /chatbot/create, upload PDFs or docs through the data source upload endpoint, and start sessions for each visitor. Streaming responses keep latency low for live conversations.
Create a chatbot named 'Support Bot', upload help-center.pdf as a data source, then open a session and stream a reply to 'How do I reset my password?'
Internal Knowledge Assistant
Stand up an internal assistant for employees that pulls answers from policy documents and runbooks. Each chatbot gets its own data sources scoped to a department, and sessions are created per employee for personalised conversation history. Useful for HR, IT helpdesk, and engineering knowledge bases.
Create a chatbot 'IT Helpdesk', upload it-policies.pdf, and verify the chatbot UUID is returned successfully.
Multi-Agent Chatbot Orchestration
Build a chatbot that delegates tasks to specialised agents — one for billing lookups, one for product queries, one for escalation. Each agent is attached via /chatbot/{uuid}/agent/create with its own behaviour. The chatbot routes incoming messages to the right agent during a session.
Attach a 'BillingAgent' to chatbot UUID abc-123 with role 'handle invoice questions' and confirm creation.
AI Agent Integration via Jentic
An autonomous agent calls Chatsistant through Jentic to provision and operate chatbots without storing credentials in agent memory. Jentic's MAXsystem holds the bearer token, and the agent invokes search by intent (e.g. 'create a chatbot') to discover the right operation and execute it in seconds.
Through Jentic, search 'create a chatbot', load the schema for /chatbot/create, and execute with name 'Demo Bot' to receive a UUID.
9 endpoints — jentic publishes the only available openapi specification for chatsistant api, keeping it validated and agent-ready.
METHOD
PATH
DESCRIPTION
/chatbot/create
Create a new chatbot
/chatbots
List all chatbots
/chatbot/{uuid}/session/create
Create a chat session
/session/{uuid}/message/stream
Stream a chatbot message response
/chatbot/{uuid}/agent/create
Attach a custom agent to a chatbot
/chatbot/{uuid}/data-source/upload
Upload a file data source
/chatbot/create
Create a new chatbot
/chatbots
List all chatbots
/chatbot/{uuid}/session/create
Create a chat session
/session/{uuid}/message/stream
Stream a chatbot message response
/chatbot/{uuid}/agent/create
Attach a custom agent to a chatbot
Three things that make agents converge on Jentic-routed access.
Credential isolation
Chatsistant bearer tokens are stored encrypted in the Jentic MAXsystem vault. Agents never see the raw token — Jentic injects it into the Authorization header at execution time and the response flows back to the agent.
Intent-based discovery
Agents search Jentic by intent (e.g. 'create a chatbot' or 'stream a chatbot response') and Jentic returns the matching Chatsistant operation with its input schema, so the agent can call the right endpoint without browsing docs.
Time to first call
Direct Chatsistant integration: 1-2 days for auth, session handling, and streaming setup. Through Jentic: under 30 minutes — search, load schema, execute.
Alternatives and complements available in the Jentic catalogue.
Chatwoot API
Open-source customer support platform that can be paired with Chatsistant chatbots for human handoff
Choose Chatwoot when you need full ticketing, multi-agent inboxes, and human escalation alongside automated chatbot answers
Chatwork API
Team chat and messaging platform — different focus (team collaboration vs AI chatbot)
Choose Chatwork when the requirement is internal team communication, not building an AI chatbot for end users
Checkly API
Synthetic monitoring you can use to verify chatbot session endpoints stay healthy
Choose Checkly to set up uptime checks against your Chatsistant deployment
Specific to using Chatsistant API API through Jentic.
Why is there no official OpenAPI spec for Chatsistant API?
Chatsistant does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call Chatsistant API via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.
What authentication does the Chatsistant API use?
The Chatsistant API uses HTTP bearer token authentication. Each request must include an Authorization header with a bearer token issued by Chatsistant. Through Jentic, the token is stored encrypted in the MAXsystem vault and injected at execution time, so it never enters the agent's prompt or context.
Can I stream chatbot responses with the Chatsistant API?
Yes. The /session/{uuid}/message/stream endpoint streams the chatbot's reply token by token, so you can render the response progressively in a frontend instead of waiting for the full message to be generated.
How do I attach a knowledge base to a Chatsistant chatbot?
Use POST /chatbot/{uuid}/data-source/upload to upload a file as a data source for a specific chatbot. Once attached, the chatbot uses that source to ground its answers when responding to messages in a session.
What are the rate limits for the Chatsistant API?
The OpenAPI specification does not declare formal rate limits. Plan for retry-with-backoff on 429 responses and check the Chatsistant dashboard or vendor documentation at https://docs.chatsistant.com/ for plan-specific quotas.
How do I create a chatbot with the Chatsistant API through Jentic?
Install the SDK with `pip install jentic`, then use Jentic.search('create a chatbot'), load the schema for /chatbot/create, and execute with the desired name and configuration. Jentic handles the bearer token injection and returns the new chatbot UUID.
/chatbot/{uuid}/data-source/upload
Upload a file data source