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AI & GenAI project

Customer Support AI Agent

Answer customer questions from your knowledge base and escalate what matters.

Advanced~10 hoursOpenAIVector DBn8nSlack

System workflow

  1. InputCustomer question
  2. AIAI + knowledge
  3. AutomationRoute + log
  4. OutputResolved reply

The problem

Support teams answer the same questions repeatedly while urgent issues wait in the queue.

The solution

A retrieval-grounded agent answers common questions from your documentation, checks its confidence, and escalates uncertain or sensitive cases to a human with full context.

Build steps

How you’ll build it

  1. 01

    Index

    Chunk and embed help articles into a vector database.

  2. 02

    Retrieve

    Find the most relevant passages for each question.

  3. 03

    Answer

    Generate a grounded reply that cites its sources.

  4. 04

    Escalate

    Route low-confidence cases to Slack with context.

Expected output

  • Indexed knowledge base
  • Grounded answering agent
  • Confidence-based escalation
  • Conversation logs for review

Tools

  • OpenAI
  • Vector DB
  • n8n
  • Slack

Skills you’ll learn

  • Embeddings & retrieval
  • Agent design
  • Evaluation
  • Human handoff

Build it in

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More projects

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  • Advanced project

    AI Research Assistant

    Summarise sources into cited research notes your team can trust.

    1. InputSources
    2. AIAI synthesis
    3. AutomationCite + check
    4. OutputResearch notes
    • Python
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    • Vector DB
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  • Intermediate project

    AI Lead Qualification Agent

    Score inbound leads with AI, sync them to a CRM and trigger instant follow-up.

    1. InputNew lead
    2. AIAI scoring
    3. AutomationCRM sync
    4. OutputWhatsApp + email
    • n8n
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See it working in the AI Lab

Describe a workflow and watch it take shape — then learn to build it for real.

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