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What this feature covers
Why it matters
The practical reason to use it.
White-label is for teams that want to sell or deliver AI without exposing the platform behind it.
How it works
A step-by-step look at the workflow.
Step 1
Start by deciding where white-label ai agent should remove friction in the conversation and which requests still need a human owner.
Step 2
Configure Custom branding and Custom domains so the feature is grounded in the same workflow context as the rest of the agent.
Step 3
Add Client workspaces so the feature can move the conversation forward without losing approval boundaries or operational clarity.
Step 4
Review Flexible pricing 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.
Custom branding
Apply your logo, colors, copy, and visual presentation across the workspace and widget so clients experience the assistant as part of your.
Custom domains
Serve the assistant from a client-specific domain so procurement, onboarding, and everyday usage stay inside the brand environment customers already recognize and.
Client workspaces
Keep each account isolated with role-based access, separate knowledge sources, and clear operational ownership so one client deployment never leaks into another.
Flexible pricing
Package setup, recurring service, and usage pricing in the way your agency or SaaS business already sells, instead of forcing every client.
Daily use
How teams use it after launch.
Workspace isolation
Separate data, prompts, and operator access per client so the branded delivery model remains safe for agencies managing multiple accounts at once.
Account ownership
Keep a clear line between what your team manages centrally and what each client can review, approve, or update inside their own.
Service reporting
Use conversation and rollout data to show clients what the assistant handled, where handoff happened, and how the branded AI service is.
Control points
What to keep controlled.
Launch on one bounded workflow
Use White-Label AI Agent on the narrowest workflow where the team can measure whether the feature reduces friction, improves clarity, and creates.
Keep the edge cases visible
Review the conversations, prompts, and system actions tied to white-label ai agent so operators can see where the rollout still depends on.
Connect the surrounding systems
White-Label AI Agent is stronger when the feature sits beside the knowledge, integrations, and routing rules that already determine what happens after.
Expand only after proof
Once the first deployment is stable, teams can extend white-label ai agent into more surfaces and agents without rebuilding the same control.
What you get
The changes teams should notice first.
- New revenue stream from AI services
- Faster client delivery with workspace approach
- Stronger relationships with integrated solutions
- Higher margins with white-label pricing
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
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White-Label AI Agent FAQ
Can I resell InsertChat under my brand?
Yes. White-label is meant for agencies and service providers that want to package the product as their own offering while keeping the client relationship, presentation layer, and commercial packaging under their own brand. It works best when the delivery model includes both setup and ongoing operational ownership. The operational question is whether white-label ai agent 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 agents, more channels, or more teams.
Do clients see InsertChat branding?
The goal is to let you present the experience under your own brand and domain, so clients experience the assistant as part of your product or service instead of as a separate third-party tool. That matters for trust during procurement, rollout, and day-to-day usage. The operational question is whether white-label ai agent 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 agents, more channels, or more teams.
Is this useful for SaaS companies too?
Yes. SaaS teams can use it when they want client-facing AI delivery to feel native to their product, especially when enterprise customers expect consistent branding, dedicated environments, and a clear owner for support and account changes. The operational question is whether white-label ai agent 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 agents, more channels, or more teams.
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