From five fragmented systems to one AI-native platform
Data scattered across five systems, none of it talking
The firm came to us with the problem most funds face: deal and portfolio data spread across five separate systems, hundreds of ingestion scripts, and no unified view. Analysts spent most of their time wrangling data instead of generating insight. Senior partners made decisions on whatever they could assemble manually.
They had invested in AI tooling, but it could not reason over data this fragmented. The same company appeared under different names in different systems. Historical context was locked in documents no one could query.
An AI-native portfolio platform, built layer by layer
We designed and shipped a platform that ingests data from LPs and portfolio companies, resolves entities across the entire deal history, and lets the team query everything in plain English. It automates the work that used to consume entire weeks: portfolio reporting, deal pattern analysis, monthly reviews, LP communications.
- Unified data architecture across 5 source systems
- Extraction pipelines for PDFs, Excel, and scanned documents
- Entity resolution across the full deal and portfolio history
- Natural language query agent over the entire corpus
- Vector search across memos, notes, and reports
- Dynamic dashboards that reconfigure to the question
- Automated monthly review and LP reporting workflows
- AI-native platform UI and product design
From data wrangling to autonomous intelligence
The platform now assembles its own reporting. Analysts moved from stitching spreadsheets to actual analysis. Partners get answers in seconds instead of waiting for someone to build the slide. The Monday morning brief writes itself.