Extend source-backed answers into your own experience
Use owned content to answer visitor questions with less friction.
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What this feature covers
Why it matters
The practical reason to use it.
The API matters when a team wants source-backed answers inside a custom surface without building separate crawling, retrieval, assistant control, and analytics infrastructure.
How it works
A step-by-step look at the workflow.
Step 1
Authenticate against the workspace and choose the assistant, source, conversation, or analytics resource your integration should control.
Step 2
Create or update assistants and source records so custom surfaces still use approved website, document, product, or support knowledge.
Step 3
Send messages, retrieve transcripts, attach metadata, or trigger webhook-style events from the systems that need visitor answer behavior.
Step 4
Review analytics and handoff outcomes so the custom integration stays aligned with website source quality and visitor needs.
Core job
The main job this feature handles.
Assistant management
Create assistants, update prompts, control privacy settings, and keep model defaults aligned with the visitor paths each team owns.
Knowledge ingestion
Upload documents, scrape websites, sync structured sources, and keep grounded answers connected to the content your business actually maintains.
Messaging endpoints
Send and receive messages programmatically, retrieve transcripts, and reuse the same conversation state across product UI, client portals, and external channels.
Analytics access
Pull usage, conversation, feedback, and tool-performance data into your own dashboards when product teams need reporting beyond the default views.
Daily use
How teams use it after launch.
JWT authentication
Authenticate once, reuse bearer tokens safely, and keep access scoped to the workspace, role, and deployment path the integration is meant to.
Webhook hooks
Send real-time events into your backend so ticketing, CRM, fulfillment, or owned routing logic reacts as conversations progress.
Channel consistency
Use one API-backed assistant across embeds, product surfaces, and custom channels instead of maintaining separate bots with conflicting logic.
Developer onboarding
The Postman collection, stable resource model, and clear request shapes shorten the path from first request to real application integration.
Control points
What to keep controlled.
What you get
The changes teams should notice first.
- Faster product integrations without rebuilding assistant infrastructure
- Cleaner backend integration with direct access to chats, sources, and analytics
- More consistent behavior across custom UIs, embeds, and client portals
- Less engineering overhead when rollout expands beyond a single channel
The facts do the selling
Plan facts, platform capabilities, and worked examples — every claim here is checkable, not a pitch.
White-label included — never a paid add-on. Copyright removal from $98/mo. Full white-label — custom domain, branded portal, your-domain emails — from $198/mo.
The white-label wedge
Platform fact
Training runs on your sitemap, PDFs, docs, and YouTube transcripts. Answers cite the source pages they came from.
Trained on your content
Platform fact
Five clients at $300/mo on a $198/mo Agency plan is $1,300+ of monthly margin before usage.
A 5-client agency on one flat plan
Worked example
Your questions, answered.
Tap any question about the product, pricing, security, or setup to see a straight answer.
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Answers about InsertChat
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API questions
What can I control through the API?
The API covers the core resources the hosted product uses, including assistants, approved sources, conversations, messages, metadata, and reporting-oriented data. The operational question is whether api makes the workflow clearer once real conversations, real ownership, and real edge cases show up. That is the bar teams should use before they expand the rollout across more assistants, more channels, or more teams.
Is the API only for custom chat interfaces?
No. Teams also use it for custom website routes, product surfaces, client portals, reporting sync, source management, and systems that need to stay aligned with the assistant layer. The operational question is whether api makes the workflow clearer once real conversations, real ownership, and real edge cases show up. That is the bar teams should use before they expand the rollout across more assistants, more channels, or more teams.
Why use the API instead of building a separate AI stack?
Using the API keeps custom surfaces on the same grounded platform as the hosted workspace, which reduces drift across prompts, approved sources, brand controls, handoff rules, and analytics. The operational question is whether api makes the workflow clearer once real conversations, real ownership, and real edge cases show up. That is the bar teams should use before they expand the rollout across more assistants, more channels, or more teams.
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