An LLM-powered trading copilot delivering sub-second market intelligence to institutional desks.
240x
Faster research cycles
62%
Inference cost reduction
99.97%
Uptime across regions
// the challenge
Ledger AI's analysts were drowning in market data spread across 14 disconnected feeds. Manual research cycles took 6+ hours per trade thesis, and the existing rules engine couldn't reason over unstructured filings, earnings calls, or news.
// the solution
We engineered a real-time RAG pipeline ingesting 40M+ documents into a vector store, fronted by a fine-tuned LLM and a streaming React dashboard. A dedicated evaluation harness benchmarked every model release against analyst-graded queries before promotion.
// the results
Within one quarter, analysts were generating fully-cited research briefs in under 90 seconds. Inference costs dropped 62% after a custom retrieval rewrite, and the platform now serves 11 institutional clients with 99.97% uptime.
// stack
