Blog

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.

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

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

Hebbia now integrates with PitchBook, bringing private-company data directly into its AI platform.

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, agents can draft longer outputs, parse denser legal documents, and reason through complex data extraction with greater accuracy than any prior model.

Hebbia, the product layer for AI, today announced a $130 million Series B led by Andreessen Horowitz.

Hebbia built Matrix, an AI platform designed to handle tasks of any complexity, across any amount of data, with full transparency into how it thinks.