POC Lab

AI proof of concepts and implementations — from idea to working system.

LiveGenAI Agent

CPC Comparison AI Agent

Competitive pricing intelligence at scale

A multi-agent system that automatically scrapes competitor websites, extracts pricing data, and generates structured comparison reports using LLM pipelines. Reduced manual research time by 90%.

Problem: Marketing team spent 2 days/week manually comparing competitor pricing across 50+ products.

Architecture Highlights

  • Multi-agent orchestration with LangGraph
  • Automated web scraping and data extraction
  • Snowflake for data warehousing and history
  • Scheduled runs with Airflow
Stack:LangGraphPythonSnowflakeGPT-4FastAPIReact
LiveRAG System

Enterprise RAG on Snowflake Cortex

Internal knowledge Q&A at enterprise scale

Production RAG system built on Snowflake Cortex Search and Cortex LLM Functions for querying internal documentation, policies, and procedures with enterprise access controls.

Problem: Employees couldn't find relevant information across 10,000+ internal documents.

Architecture Highlights

  • Snowflake Cortex for native vector search
  • Hybrid search (semantic + keyword)
  • Role-based document access control
  • Citation and source attribution
Stack:Snowflake CortexLangChainFastAPINext.jsPython
POCData Platform

AI Data Quality Monitor

Intelligent data validation and remediation

AI-powered data quality system that detects anomalies, classifies issues, and suggests remediation actions using Claude API. Integrated with Informatica IDMC for automated fixes.

Problem: Data quality issues were discovered late in the pipeline, causing costly downstream failures.

Architecture Highlights

  • LLM-powered anomaly classification
  • Informatica IDMC integration for remediation
  • dbt test suite auto-generation
  • Alerting with severity scoring
Stack:Claude APIPythonInformatica IDMCdbtSnowflake
In ProgressGenAI Agent

Multi-Agent Workflow Orchestrator

Autonomous business process automation

Hierarchical multi-agent system for automating complex business workflows — document processing, data extraction, validation, and downstream system updates with human-in-the-loop checkpoints.

Problem: Manual document processing for onboarding required 3 FTEs and a 4-day turnaround.

Architecture Highlights

  • Supervisor-agent pattern with LangGraph
  • Human-in-the-loop approval gates
  • Document parsing with vision models
  • Complete audit trail and observability
Stack:LangGraphPythonGPT-4MongoDBFastAPIReact

Explore the Code

Some POCs have public repositories on GitHub.

GitHub Profile