Enterprise LLM Extraction Pipeline

AI-powered intelligence extraction from unstructured data. Maps entire organizations in under 20 minutes. Deployed at a top-3 consulting firm.

PythonCUDAPostgreSQLVector DBFastAPI

THE PROBLEM

A top-3 management consulting firm needed to map the leadership structure of target companies from unstructured public data - faster and more accurately than their analysts could do manually.

OUR APPROACH

We built a multi-stage LLM pipeline that crawls, extracts, deduplicates, and assembles organizational hierarchies. GPU-accelerated inference handles thousands of documents in parallel, with a vector database for entity resolution.

TECHNICAL DEPTH

01Multi-stage LLM pipeline: crawl, extract, deduplicate, assemble

02GPU-accelerated batch inference for document processing

03Vector similarity for entity resolution across sources

04Hierarchical relationship inference with confidence scoring

05REST API with sub-second query latency on assembled graphs

OUTCOME

Maps 5,000-person organizations in under 20 minutes. Deployed in production at the client.

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