Train on Your Content
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 agent builder is the part of InsertChat that turns a raw idea into a production assistant.
How it works
A step-by-step look at the workflow.
Step 1
Start by deciding where branded ai assistant builder should remove friction in the conversation and which requests still need a human owner.
Step 2
Configure Prompt and behavior and Prompt templates so the feature is grounded in the same workflow context as the rest of the.
Step 3
Add Conversation context so the feature can move the conversation forward without losing approval boundaries or operational clarity.
Step 4
Review Model selection in production, then refine the configuration until the feature is improving both response quality and the next-step handoff.
Core job
The main job this feature handles.
Prompt and behavior
Set prompts, temperature, and behavior per agent.
Prompt templates
Start from templates and fine-tune your prompt.
Conversation context
Agents use chat history to stay consistent and helpful.
Model selection
Choose models behind the branded experience.
Tool enablement
Turn on CRM, support, ecommerce, search, and handoff tools when needed.
Visitor insights
Review questions, unanswered topics, leads, and content gaps.
Daily use
How teams use it after launch.
Full UI customization
Customize colors, logos, and bubble position.
Layouts and styling
Choose bubble or window layouts and match your brand.
Conversation controls
Pin, rename, and manage chats.
Webhooks and metadata
Send events and enrich conversations with metadata.
Control points
What to keep controlled.
Workspace roles
Assign roles like owner, admin, manager, or client.
Agent assignments
Grant access to specific agents per teammate.
Privacy controls
Keep data isolated per workspace and agent.
What you get
The changes teams should notice first.
- Faster launches without rebuilding experiences
- More consistent answers across agents and teams
- Cleaner handoffs with the right context captured
- Safer workflows with controlled tool access
What our users say
Businesses use InsertChat to launch branded assistants faster and keep their knowledge in one branded AI assistant.
Finally, one place for all my AI needs. The ability to switch models mid-conversation is game-changing.
Sarah Chen
Product Designer, Figma
We deployed AI support in 20 minutes. Our response time dropped by 80%. Customers love it.
Marcus Weber
Head of Support, Notion
The white-label option let us offer AI services to our clients overnight. Revenue grew 40% in Q1.
Elena Rodriguez
Agency Founder, Digitale Studio
Try the FAQ like a visitor.
Open product, pricing, security, integration, and free-tool questions in the same chat your visitors use.
InsertChat
Interactive FAQ
Hey. Pick a question below and see how InsertChat turns FAQs into clear, source-backed answers.
Branded AI Assistant Builder FAQ
How do teams usually adopt branded ai assistant builder first?
Branded AI Assistant Builder usually starts with one workflow where the team can measure the effect quickly, such as a support queue, sales handoff, or onboarding flow. That keeps the rollout concrete instead of trying to change every conversation at once. Once the first deployment is stable, teams can expand the same pattern to more agents and channels with much less rework.
What should branded ai assistant builder connect to in InsertChat?
It should connect to the parts of the workspace that keep the feature grounded in real operating context, especially knowledge base and the knowledge or workflow systems that shape the response. That is what turns branded ai assistant builder from a feature flag into something the team can trust in production. The goal is to keep the next step visible, not just make the interface look more complete.
Why does no-code builder matter when using branded ai assistant builder?
No-Code Builder matters because branded ai assistant builder only becomes useful when the surrounding rules are clear. Teams need to know what the feature should do, what it should not do, and how it should hand work off when the workflow becomes more complex. That clarity is what keeps the feature reliable after launch instead of becoming another source of manual cleanup.
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3-day free trial · No charge during trial