Hebbia

Process millions of documents at once, with transparent and trustworthy AI results, to automate and accelerate document-based workflows.
Large Language Model Automated Workflows Knowledge Management

Hebbia provides a Large Language Model (LLM) platform that lets people work side by side with AI agents, asking complex questions and ingesting vast quantities of data. Matrix, the foundation of Hebbia, is a workflow engine that can run many steps on any number of data sources. It converts user requests into concrete processes, increasing productivity and accuracy.

Hebbia overcomes the shortcomings of traditional LLMs that can only process one file at a time or search engines that only return a few top results. Matrix lets you ask questions of all your documents at once, even if you have millions of them. That's why it's good for financial due diligence, market research and knowledge management.

Among Hebbia's features are:

  • Multi-file processing: Can process millions of documents at once.
  • Trustworthy AI: Shows its work step by step so you can check and trust AI results.
  • End-to-end encryption: Keeps sensitive information private.
  • Automated workflows: 10x faster and more accurate document-based workflows.
  • Modality flexibility: Can handle different types of data, including images and tables.

Hebbia is geared for large enterprises, financial services companies, governments and law firms, where it can help automate work and improve decision making. Customers say they've cut hours out of their work and improved their jobs.

Hebbia is good for industries like financial services, law and pharma, where it can help professionals extract, process and analyze unstructured files. It can integrate with data rooms and use a variety of LLM sources, including OpenAI and Anthropic.

There's no pricing information, but you can sign up for a waitlist or contact Hebbia for more details. With its potential to transform knowledge work, Hebbia could change the lives of billions of humans every day.

Published on June 14, 2024

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