Customer Risk Early-Warning System

What it does:
Scans customer messages, support tickets, and payment delays daily → flags high-risk customers → fetches relevant contracts/SOPs (RAG) → alerts CX head with a suggested action plan.

Why it’s perfect:

• Appeals to customer-focused, risk-aware leaders.
• Brings urgency and real-time automation feel.
• Uses embedded company data (contracts, old tickets) as RAG base.
• Adds escalation/approval path (Guardrail) before actions.
• Vector DB brings personalized recommendations.

Concepts covered:
Sentiment analysis, RAG, guardrails, vector DB, multi-agent

Feels like: Building a Customer Retention Copilot

Internal Knowledge Assistant for Teams

What it does:
An agent that employees can ask questions to — it pulls from internal training docs, meeting notes, and SOPs using RAG and vector DB. Logs usage patterns, escalates complex queries, and generates a weekly insights report for leaders.

Why it’s perfect:

• Great for strategy or HR leaders who want to scale enablement.
• Covers RAG, vector DB, context flow (MCP) and analytics.
• Involves long memory (MCP) for escalations.
• Adds “guardrail” to escalate unknowns to managers.

Concepts covered:
Vector DB, RAG, multi-agent query-to-summary, Guardrails, MCP

Feels like: Building a Company Wiki Copilot with alerts

Project 1: Dynamic Returns Handler

• Goal: Automate return/refund workflows.
• Agentic Components:
  
  • Multi-agent workflow:
    
    • Validator Agent: Checks return eligibility (RAG on policy + order history).
    • Logistics Agent: Generates shipping labels; updates inventory.
  • Guardrails: Escalates disputes to staff.
• Deployment: Shopify app + Fedex API integration.

Project 2: Personalized Upsell Bot

• Goal: Increase cart value via real-time recommendations.
• Agentic Components:
  
  • RAG: Leverages product catalogs and user behavior data.
  • Prompt Engineering: "Tree of Thought" to optimize suggestion sequences.
  • Tooling: Applies discounts; tracks conversion metrics.
• Deployment: Chat widget (Dialogflow) + BigQuery analytics.

Smart Email Triage & Response Agent

What it does:
Scans leader’s inbox, tags and prioritizes messages, fetches response guidelines (RAG), drafts replies for review, and only sends after the leader’s approval. Can escalate certain emails to relevant team heads.

Why it’s perfect:

• Super relatable, as every leader drowns in emails
• Delivers instant time savings
• Involves RAG, guardrails, multi-agent routing, vector search

Concepts covered:
RAG, Guardrails, vector DB, AI summarization, logic

Feels like: Building an Executive Email Copilot