Chat with Your Enterprise Data - AI Data Analytics

Created by team Abrar14 on May 16, 2026
Data & Intelligence

Chat with Your Data is an enterprise analytics platform that transforms how organizations interact with their data. Built for Track 4: Data & Intelligence, it delivers complete coverage of all five focus areas: RAG over multi-source data, natural language querying, knowledge graph extraction, anomaly detection, and AI-powered data pipelines. The system leverages Gemini 2.5 Flash in three powerful ways: native function calling for database queries (eliminating SQL hallucinations), knowledge graph extraction from PDF documents, and Google Search grounding for cross-source question answering. Every query is processed through Veea's LobsterTrap security firewall, which inspects prompts before they reach the AI, blocking prompt injection, PII requests, and data exfiltration attempts with only 50ms overhead. Our core innovation is a deterministic SQL builder that generates perfect queries from natural language, ensuring dashboard numbers, chat answers, and monitoring alerts always match—solving the consistency problem that plagues traditional AI analytics. The system processes 24 KPIs through parallel execution, delivering sub-2-second dashboard loads and 3-8 second chat responses. Five integrated features demonstrate production readiness: an executive dashboard with real-time KPIs, a conversational chat interface, four-layer anomaly detection, document intelligence with interactive knowledge graphs, and security diagnostics with live canary tests. The architecture scales from 13 properties to thousands without modification, handles years of historical data, and maintains enterprise-grade security throughout. Built with Streamlit, Supabase PostgreSQL, and deployed on Hugging Face Spaces, the system is immediately accessible and demonstrates how Gemini's intelligence combined with Veea's security creates enterprise-ready AI solutions. Business impact includes 70% analyst time savings, zero SQL errors, 100% data consistency

Category tags: