Overview
SketricGen provides a high-performance Public API service that enables AI-powered conversational workflows using custom agents you design in the Web App. This API provides endpoints for running AI workflows, managing conversations, and streaming real-time responses. Base URL:https://chat-v2.sketricgen.ai/api/v1
When to Use the Public API
Use the Public API when you want to call a SketricGen agent from your own product, backend, workflow runner, or custom UI. Common use cases:- Run AI Workforce agents from your own application
- Add SketricGen agents to an internal product experience
- Build a custom chat UI instead of using the hosted website widget
- Trigger an agent from backend jobs or server-side automations
- Keep conversation identity aligned with users or contacts in your own system
Authentication
All API requests require authentication via an API key in the request headers. Required Header:Endpoints
Run Workflow
POST/run-workflow
Execute an AI workflow using a specified agent to generate intelligent responses based on user input.
Request Headers
Request Body
Example Request
Contact ID and User Grouping
Usecontact_id when your product already knows who the end user or contact is. Conversations sent with the same agent_id and contact_id are grouped under the same contact in SketricGen.
This is useful when you want to:
- See all conversations from one customer or app user together
- Continue reviewing a user’s history across multiple sessions
- Connect SketricGen conversations back to your CRM, database, or product user record
- Use the same identity model across API, widget, iframe, and other channels
Identity Fields by Deployment Method
The same agent can be deployed through the website widget, iframe, fullscreen link, or Public API. The identity fields change slightly by deployment method:
API example:
contact_id create conversations without your external user mapping.
Response Formats
The endpoint supports two response modes.1. Standard Response (stream: false)
HTTP Status:201 Created
Response Body:
Example Response:
2. Streaming Response (stream: true)
HTTP Status:200 OK
Content-Type: text/event-stream
When streaming is enabled, the endpoint returns real-time Server-Sent Events (SSE) as the AI processes the request.
Event Types:
Example Streaming Events:

