AI Laboratory
Experiments at the Frontier of AI + Data
Exploring agentic AI, LLM integrations, and intelligent automation in the data analytics space. Each experiment pushes the boundary of what's possible when AI meets enterprise data.
AI-Powered BI Copilot
Built an intelligent chatbot integrating LLMs with Power BI semantic models via MCP (Model Context Protocol) servers. Users query business data using natural language and receive instant visualizations.
Autonomous Analytics Agent
Developed an agentic AI system that monitors data quality, detects anomalies, and automatically generates executive summaries. The agent runs scheduled analysis and pushes findings to stakeholders.
LLM-Powered Data Query Engine
Created a natural language to SQL translator powered by Claude that understands business context and semantic model metadata, generating optimized DAX and SQL queries from plain English.
AI Data Quality Monitor
AI-driven data reconciliation and validation that learns expected patterns and flags anomalies in data pipelines, reducing manual QA effort significantly.
Conversational Dashboard Builder
Exploring AI that can generate Power BI report layouts and DAX measures from natural language descriptions of business requirements.
Self-Healing Data Pipelines
Investigating AI agents that detect pipeline failures, diagnose root causes, and implement fixes autonomously with human-in-the-loop approval.
The future of analytics is conversational, agentic, and self-healing.
I'm building toward a world where business users interact with data through natural language, AI agents autonomously monitor data quality, and analytics platforms self-optimize based on usage patterns. Every experiment here is a step in that direction.