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# AIFAQ Lab Workshop (LFDT)

Host: Linux Foundation Decentralized Trust (LFDT)
Project: AIFAQ Lab — Enterprise AI Assistant, Snowflake, Multi-Agent RAG, GitMesh
Format: Live demo + hands-on walkthrough + Q&A (virtual)

## Workshop Title

Building an Enterprise AI Assistant with Multi-Agent RAG (AIFAQ Lab)
Learn how AIFAQ Lab turns scattered enterprise knowledge into secure, conversational workflows using multi-agent Retrieval-Augmented Generation (RAG). In 90 minutes, we’ll cover the reference architecture, data governance patterns, Snowflake-native packaging considerations, and a live demo of agent collaboration for real business tasks—then guide you through a hands-on prompt + evaluation exercise.

## Who Should Attend

  • Engineering & Data Leaders: CTOs, Heads of Data/AI, Platform Engineers
  • Builders: ML/AI engineers, Data engineers, Solutions architects
  • Domain Teams: Product, Support/Success, Compliance & Security stakeholders

## Key Takeaways

  • Architecture: How multi-agent RAG differs from single-agent chat; orchestration patterns, guardrails, and observability
  • Data Governance: IP preservation, PII controls, retrieval quality, and evaluation loops
  • Packaging: What changes when targeting Snowflake Native App delivery and Marketplace listing
  • Hands-On: Prompt + context design, error analysis, and a simple eval scorecard you can reuse

## Agenda (90 minutes)

  1. Welcome & LFDT Context (5 min)
  2. AIFAQ Lab Overview & Roadmap (10 min)
  3. Architecture Deep Dive (Multi-Agent RAG) (20 min)
  4. Live Demo: Agents Collaborating on a Real Task (15 min)
  5. Hands-On Mini Lab: Prompting & Quick Eval (20 min)
  6. Operationalizing: Security, Cost, and Snowflake-Native Path (10 min)
  7. Q&A and Next Steps (Contribute, Pilot, Partner) (10 min)

## Speakers

  • Gianluca Capuzzi — Co-Founders AIFAQ
  • Ryan, Sumana, Jayaram, Lochan — LFDT Mentee / Enterprise Advisor or Design-Partner Representative

## Prerequisites

  • Basic familiarity with LLMs, embeddings, and vector search
  • A modern browser; GitHub account if you’d like to follow along with example prompts/evals

## What You’ll Receive

  • Slides & architecture diagrams
  • A prompt/evaluation template (copy-ready)
  • Links to the AIFAQ Lab repo, issues, and contribution guide

## Call to Action

  • Register to receive the Zoom link and workshop materials.
  • Interested in piloting AIFAQ Lab or contributing? Bring a use case—we’ll share the intake form at the end.

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