This phase is about putting your tested AI agent in front of real customers. Once you’ve validated answers in the Playground, the next step is to embed the agent into your support channels.
Think of this phase as your go live moment — the point where your AI moves from testing behind the scenes to supporting real customers.
Types of AI Support Agent Implementation
There are two main ways to integrate AI into support:
Agent-facing integrations – AI copilots suggesting answers to agents. Common in the past when AI was less reliable.
Customer-facing integrations – AI interacts directly with customers. This is today’s standard and the focus of this guide.
Customer-facing integrations give users instant answers from your documentation or systems, without waiting for a human.
Steps
1. Choose your first channel
Decide where your AI agent should appear first.
Why it matters: A focused rollout gives you early value without adding too much complexity.
Options:
Website widget in your help center, product documentation, or developer portal
In-product widget inside your SaaS dashboard
Community bot in Slack or Discord
Live chat integration with Intercom or Zendesk
Ticketing or email integration
Integration type summary:
Integration type | Channel / Location | Primary use case |
Website widget | Docs, knowledge base, help center, developer portals | Self-service support based on product documentation |
In-product widget | SaaS UI / dashboard | Real-time support inside the product workflow |
Community bot | Slack / Discord | Customer support inside active communities |
Live chat | Intercom, Zendesk (chat) | AI as frontline for chat: greet, resolve, escalate |
Ticket/email | Email, ticket forms | Automate first responses, filter spam, smart routing |
Example table comparing available channels (website, in-product, community, live chat, ticketing).
2. Embed in Website / Knowledge Base / Developer Docs
Add a self-service widget where customers already look for answers.
Why it matters: Customers get reliable support without leaving your site or app.
Options:
Help center widget → embed in your knowledge base for instant Q&A
Product documentation or developer portal → give developers direct access to API or feature details
In-product widget → let users ask questions while using your SaaS product
3. Embed in Helpdesk
Integrate the AI into your support system.
Why it matters: The AI becomes the frontline, resolving repetitive requests before humans step in.
Options:
Live chat integration (Intercom, Zendesk): AI greets and tries to resolve common issues, escalates if needed.
Ticketing or email integration: Sends instant first responses, filters spam automatically, and routes unresolved cases with full context.
4. Keep scope clear
Limit the agent to the general questions it already handles well.
Handle only documentation-based, product-related questions
Escalate sensitive or account-related requests to humans
Record rollout scope so your team knows what to expect
5. Monitor first interactions
Review early live conversations after embedding.
Review conversations in Chatlogs (filter by “escalated” or “fallback”)
Check fallback and escalation rates
Adjust knowledge base, Q&A, or escalation rules as needed
Best Practices / Tips
Start with one channel (commonly website widget or live chat).
Make it clear to customers when they’re speaking with AI.
Set strict escalation rules so users never get stuck.
Involve your support team in reviewing early conversations.
Expand to additional channels only after the first is stable.
Common Mistakes to Avoid
Launching across all channels at once.
Letting the AI handle cancellations, billing, or legal requests.
Forgetting to review early interactions in Chatlogs.
Skipping internal communication — your support team should know the AI is live.
Embedding without clear escalation triggers.
Cross-references
Chatlogs (to review early interactions)
✅ Expected outcome: AI agent is embedded into live channels with safe escalation to humans.