Case Study: Hebbia helps knowledge workers save thousands of hours with Claude

Hebbia helps knowledge workers save thousands of hours with Claude

Hebbia, an AI platform for knowledge work, helps financial and legal professionals analyze complex documents, but their customers faced a major challenge. Traditional methods were unable to handle the nuance and scale required to extract meaningful insights from thousands of dense documents. According to their Product Manager, basic AI tools failed on 84% of real-world queries that required multi-step reasoning across multiple documents.

To solve this, Hebbia integrated Claude to power its platform. They used Claude, particularly the Sonnet model, for meta-prompting to automatically generate optimal prompts for complex analysis, eliminating the need for users to master prompt engineering. The solution dramatically accelerated performance; by leveraging Claude's prompt caching for repeated document analysis, Hebbia achieved up to an 85% reduction in response times. This allows their customers, including over a third of the top 50 asset managers, to get deep, actionable insights from hundreds of documents simultaneously and in real-time.

Hebbia

Divya Mehta

Product Manager