finance_ops · logistics · workflow
Finch: Uber's Conversational AI Data Agent for Real-Time Financial Insights
Uber's financial analysts faced slow, inefficient data access requiring manual searches across multiple platforms, complex SQL query writing, or data request submissions that could take hours or days — causing delays that impacted real-time decision-making.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · User query in Slack
A finance team member asks Finch a question in Slack using natural language.
Tools used
FinchRAGLangChain LanggraphOpenSearchSlackGenerative AI GatewaySlack AI Assistant APIsPrestoIBM Planning AnalyticsOracle EPMGoogle Sheets
Outcome
Finch eliminates friction in financial data retrieval for Uber finance teams by enabling conversational natural language queries in Slack, leading to less friction, fewer delays, and faster data-driven decisions.
Grounding & classification
Source type: technical build writeup
32 fields verified against source quotes, 1 dropped as unverifiable.
agentic workflowconversational aidata extractionenterprise searchmulti agent workflowragknowledge basebuilder submittednamed customerproduction runtime claimedtools describedworkflow describedlogisticssoftwarecycle time reductionemployee productivitytechnical build writeupback office opsfinance opsagentic task executionrag answering