Configured Agents for Vertical Workflows

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Danny Wheller, VP of Business & Strategy at Hebbia, on vertical vs horizontal enterprise AI

Interview
the antithesis of an agent is something that's just an LLM wrapper
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The real dividing line is whether the software helps finish a job or just answers one prompt. In this framing, an LLM wrapper is a single step tool, ask a question, get text back. An agent is a work system, it pulls from many documents, breaks a larger task into smaller steps, uses tools or other agents, and produces something usable like a diligence matrix, memo, or contract review.

  • Hebbia built Matrix as both the user interface and the orchestration layer. Teams use it like a spreadsheet for repeated work, where rows, columns, and cells can trigger retrieval, reasoning, calculations, and draft generation across large document sets.
  • This is why Hebbia can coexist with search products like Glean. Search finds files and answers lightweight questions. Hebbia is sold for the next step, turning source material into work products in finance and legal, where accuracy, audit trails, and human review matter.
  • The business implication is pricing power and narrower deployment. Thin wrappers tend to look like cheap seats for broad use. Hebbia instead prices a smaller group of power users at $10,000 per year to build and maintain agents, then sells lighter seats for consumers of those workflows.

The market is moving from chat interfaces toward configured systems that mirror how teams already work. As models improve, the durable layer shifts from the model itself to document access, workflow design, verification, and domain specific templates. That favors products that can turn repeated expert tasks into reusable operating machinery.