Post by ByteByteGo

💬 How Uber Built a Conversational AI for Financial Analysis For Uber’s finance teams, getting answers from data once meant juggling multiple tools, writing SQL queries, and waiting hours for data requests. Today, it takes just one message in Slack. This is made possible by Finch - Uber’s conversational AI data agent. Finch is built to bring real-time financial intelligence directly into the daily workflow of analysts. When a user asks a question, Finch automatically identifies the right data source, generates a SQL query, checks access permissions, and delivers the answer instantly inside Slack. At its core, Finch is powered by: 1 - Curated financial data marts for reliable and structured data. 2 - A semantic layer built on OpenSearch that maps natural language to database columns for accurate query generation. 3 - An agentic workflow using LangChain and LangGraph, where specialized agents like the SQL Writer and Supervisor work together to understand, plan, and execute queries. 4 - Slack SDK and Google Sheets Explorer for seamless interaction and data sharing. By combining curated financial data, a semantic layer, and an agentic workflow, Finch delivers real-time analysis directly inside Slack. 🔗 Read the full breakdown: https://lnkd.in/e8BB8jSP Supported by our partners helping engineering teams build fast, reliable data systems that power real-time applications: Redpanda - a modern streaming platform designed for high-throughput, low-latency data pipelines. ➡️ https://bit.ly/4oXHjMH