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$20

AI Customer Support Agent

Build an AI agent that triages support tickets, classifies intent, retrieves answers from your knowledge base, and escalates to humans when confidence is low.

"My account login isn't working after the password reset — can you help?"

6 Interactive Sessions

Short, interactive sessions — watch it work, steer it, then build it yourself. Go deeper anytime with the full code walkthrough.

  1. 1

    The Data Lake — five source types, one searchable shape

    Before an agent can answer a single ticket, the answer — which already exists somewhere — has to become findable: five support sources normalized into one unified store with the metadata that later powers routing and retrieval.

  2. 2

    Classification — a sentence becomes something routable

    Turn a raw sentence into a structured, routable profile: what does the customer want (intent), how urgent is it (priority), what area is it (topic), and what concrete things did they mention (entities)?

  3. 3

    Knowledge Retrieval — the right passage, not fifty docs

    Get the one right passage for the customer's question — an FAQ fast path for common questions, hybrid search with source-authority boosting and popularity signals for the rest, and snippet extraction so the answer is the relevant paragraph, not the whole article.

  4. 4

    Response Engine — answer, or escalate with context

    The agent has a draft answer. Should it send it or hand to a human? High-confidence, routine and safe → auto-respond. Low-confidence, sensitive, or with no good source → escalate to a human, carrying the full context. Knowing which is the whole game.

  5. 5

    The Support Desk — the pipeline becomes a product

    Wire the whole pipeline into a chat app: the customer types, a classification badge appears, the retrieved sources show, the answer streams — and when it escalates, the escalate button hands the human the full context, not a blank slate.

  6. 6

    Deploy & Monitor — is it actually helping?

    Ship the agent to the channels customers live in (Slack, email, chat), then watch the numbers that tell you whether it's helping — resolution rate, CSAT, escalation rate, time-to-resolve — and close the loop by feeding low-CSAT answers back into the knowledge base.

Production patterns you'll master

Intent ClassificationRAG PipelineEscalation RulesTicket RoutingObservability

Synthetic data included

  • Support ticket exports (2,000 tickets)
  • Knowledge base articles (150 articles)
  • Product documentation (PDFs)
  • Escalation rules (JSON)
  • Customer satisfaction surveys

What you walk away with

Shareable portfolio

A public URL showing your module timeline, patterns mastered, and completion status.

All the code

Download everything as a ZIP — pipelines, guardrails, deployment configs. Yours forever.

Module walkthrough

Each module documented with deliverables and the production pattern you implemented.

Ready to build your ai customer support agent?

First course free. $20 per course after that.