
Corporations are drowning in data but starving for immediate insight. Traditional Business Intelligence (BI) workflows require data engineering pipelines, complex SQL dashboards, and manual assembly of PowerPoint presentations just to share weekly updates. Business leaders lose critical windows of opportunity waiting for static reports that fail to offer interactive depth. Abi is an automated enterprise BI assistant that bridges the gap between raw corporate data and presentation-ready insights. Users simply connect their data sources and organize them into workspace folders. Abi instantly takes over, allowing users to explore their data through intuitive conversational chat or automatically spin up comprehensive, publication-grade analytical reports. The core architectural engine is built using LangGraph, establishing a modular, robust multi-agent pipeline. It features: Dynamic Intent Classification: An intelligent routing system that determines whether a user needs a casual data answer or a deep-dive report pipeline. Autonomous Sandbox Exploration: A secure Python REPL environment where the agent writes, tests, and executes Pandas code directly against datasets (like our functional supermarketsales.csv deployment) to pull real-time calculations without risking data exposure. What We Built & The Future Roadmap Due to the hackathon timeline constraints, our current submission showcases the critical validation engine: a fully functional conversation analyst node that dynamically ingests, queries, and interprets complex retail transactions. The groundwork is explicitly laid for Abi's definitive killer feature: transforming structured dashboard data into fully automated document reports (.pptx, .pdf, .xlsx) and automatically synthesizing them into a synthetic video presentation. Abi turns static numbers into a shareable, human-like data briefing video with a single click. Abi is the future of hands-free corporate reporting.
13 Jul 2026