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KNOWLEDGE RETRIEVAL · AUTOMATION

Business AI & RAG

Company-approved knowledge, useful answers, and a clear path to a human when it matters.

TypeScriptNext.jsSupabaseLLM integrations

01 / THE PROBLEM

A useful starting point.

Customer-facing teams need consistent answers grounded in their own knowledge, with a clear route to human support.

02 / MY CONTRIBUTION

Connecting the pieces.

I designed a business AI agent using Retrieval-Augmented Generation over company-approved knowledge to answer customer inquiries and qualify sales opportunities.

SYSTEM FLOW · SIMPLIFIED

  1. 01Customer inquiry
  2. 02Knowledge retrieval
  3. 03Grounded response
  4. 04Human handoff

03 / ENGINEERING DECISIONS

Approved knowledge first

Used retrieval over company-approved information to provide relevant context for customer responses.

Structured workflows

Built tool-assisted workflows for routine support and inbound sales qualification.

A human in the loop

Included an explicit handoff protocol so conversations can move from automation to a human.

04 / THE RESULT

Built for a real use case.

An intelligent business support system combining knowledge retrieval, customer inquiry handling, sales qualification, and human escalation.

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