Introducing Headless Hebbia
Every firm has knowledge spread across documents, emails, databases, and internal systems. Whether a team is building its own application or using an AI assistant, even the best models need the right context from that information to do useful work.
Getting that context into an application takes work. Teams have to find relevant sources, understand the relationships between them, coordinate analysis across steps, and check the results.
That’s the work we’ve focused on at Hebbia. Today, we’re introducing Headless Hebbia: our API and MCP server. They bring Hebbia’s retrieval, orchestration, and analysis into bespoke applications we build with customers and the AI assistants their teams already use.
We picked a pretty good month to go “headless.”
Retrieve and analyze at scale
Hebbia works through a question step by step, retrieving and analyzing the information it needs along the way. Developers can test the workflow, and users can check the findings against the source material.
The relationships between sources are critical here. A question about a company may depend on its subsidiaries, previous transactions, or notes filed under a different name. We work with customers to map those relationships and account for the firm’s own terminology and classifications. That helps retrieval find relevant material that a search for the company’s name alone would miss.
Hebbia supplies relevant evidence to each model call as the analysis progresses. This lets an application work across a large collection while using smaller context windows where appropriate.
Build applications with your team
A banking team may want an origination tool that traces a newly announced deal to downstream effects on its coverage universe. Hebbia can build an application that triggers on the announcement and draws on research, market maps, and internal notes to surface the right client to call, the reason to call now, and the pitch to make. Every claim links to evidence the banker can review.
A professional services team advising on an acquisition needs to understand the cost of integrating the target’s technology. We can connect system records, contracts, and workshop notes to identify consolidation opportunities and integration risks, with supporting evidence available in the firm’s own client portal.
We work with each team to define the analysis, connect the relevant information, and build the application around its process. That includes how the firm interprets its records and where people need to review the results. Customers can use Hebbia’s intelligence entirely through an interface built for them (or by them).
Connect your existing AI tools
Through MCP, assistants such as Claude and ChatGPT can call Hebbia to retrieve and analyze a firm’s connected information, returning answers with the supporting evidence. The choice of model and interface stays with the firm.
If you’re building an internal application or want your existing AI tools to work better with your firm’s knowledge, talk to us about what we can build together.
