Hebbia

Hebbia is an AI-powered research workspace aimed at people who need to work through large volumes of documents quickly. Rather than asking a single chatbot to recall fACTs, Hebbia lets users load their own files, filings, transcripts or datasets into a structured workspace and then APPly AI to extract, compare and summarize Information across that corpus. It is positioned for finance, legal, consulting and other knowledge-heavy teams where speed and traceability matter.

What it does

The platform combines document ingestion with AI models that can read Long Contexts and answer questions against user-supplied material. Users typically upload a set of files or connect a data source, DeFine a Prompt or task, and let the system process each document before aggregating results into a table, matrix or report. The goal is to turn slow manual review into a repeatable, auditable Workflow.

Key capabilities

• Multi-document analysis: Apply the Same question or instruction across hundreds of files and collect structured ouTPUts.
• Cited answers: Responses are Generally linked back to source passages so reviewers can verify claims.
• Matrix and table extraction: Build Comparison grids or data tables from unstructured text such as PDFs and transcripts.
• prompt-based workflows: Save and reuse task templates for recurring research processes.
• team collaboration: Shared workspaces support review by multiple users, though exact roles may vary by plan.

Who it is for

Hebbia is most relevant to Investment analysts conducting due diligence, lawyers reviewing contracts, consultants synthesizing research, and Operations teams that regularly process large document sets. It is less suited to casual users seeking a general-purpose chatbot, because its value depends on having a real document corpus and a defined research task.

How to get started

1. Request access through the vendor; Enterprise onboarding is commonly required.
2. Create a workspace and upload or connect your documents.
3. Write a task prompt that specifies the output fORMat you need.
4. Run the analysis, then review citations and refine the prompt as needed.
5. Export results or share them with collaborators.

Pricing and access caveat

Hebbia is generally offered as a paid, enterprise-oriented product, and public pricing details may not be listed, so costs are likely quote-based. trial availability, plan structure and feature liMITs may vary and should be confirmed directly with the vendor. Access from some regions may require network configuration. Users should also verify data-handling and compliance terms before uploading sensitive material.