Blog

This month’s platform improvements cut friction, speed up analysis, and unlock new ways to move deals forward.

As OpenAI’s research partner for financial services agents, we’ve spent weeks challenging GPT-5 on the most complex investing and banking workflows.

We built a multi-agent system that goes beyond public web search to synthesize insights for any data source, including proprietary data sources.

From ramping coverage to building a searchable knowledge bank, here’s how leading equity research teams use Hebbia to move faster without sacrificing depth.

From credit agreement analysis to pitch deck development, here’s how LevFin teams use Hebbia to cut the manual work out of diligence and move deals faster.

From CIM creation to diligence Q&A, here’s how leading investment banking teams use Hebbia to cut manual work out of every stage of the deal cycle and execute with more speed and precision.

Hebbia acquired FlashDocs, the leader in generative slide creation, so customers can turn AI-powered research and analysis directly into fully branded PowerPoint decks in seconds.

At the end of last year, we returned to the drawing board and redesigned Matrix Agent.

The internet decoupled labor from geography. Now AI is decoupling labor from humans, and George explains what that means for how organizations are built.

We built a distributed LLM request scheduler that intelligently routes billions of tokens per day across multiple providers so high-priority work always gets through, even under rate limits.

After pioneering semantic search and RAG, we found both fell short on the hardest questions so we scrapped them and built a new information retrieval system from scratch.

With OpenAI o1 now integrated into Matrix, Hebbia’s agents can draft longer outputs, parse denser legal documents, and reason through complex data extraction with greater accuracy than any prior model.