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Hyperscience

Hyperscience focuses on Automation → Document AI → Analyze workflows.

shipped Nov 14, 2025analyzepaid
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AnalyzeDocument AIAutomation
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1Analyze
2Document AI
3Automation

Stork Quadrant

Sleeping Giant· 38/100

Has a real moat but invisible to agents. Add an MCP and you'd climb.

Hyperscience's defensibility rests on three real moats: regulatory (HIPAA, SOC2 compliance in workflows where liability matters), proprietary training data from millions of documents processed, and coordination rails that orchestrate human review, exception handling, and downstream system integration. An LLM alone can extract text and classify documents, but can't bear the liability for a loan application or insurance claim, can't manage the human-in-the-loop workflows at scale, and lacks the domain-specific training data Hyperscience has accumulated. The core risk is that as LLMs improve at document understanding, the gap narrows—but the coordination and trust moats buy real time.

Claude Haiku 4.5, scored 2026-05-25

Defensibility · 57/100

  • Physical-world coupling
  • Regulatory moat
  • Network liquidity
  • Proprietary refreshing data
  • High-trust catastrophic workflows
  • Multi-party coordination
  • Brand / community / taste

An LLM alone could replace

  • Extract structured data from a single document image using OCR and field mapping
  • Classify document types based on visual features and content patterns
  • Generate a summary or key-value pairs from unstructured document text

Agent-Readiness · 15/100

  • Verified MCP
  • Listed on agent surfaces
  • Usage-based pricing
  • Headless agent auth
  • Public OpenAPI
  • Active changeloghttps://www.hyperscience.com/blog/ (2026-05-20)
  • llms.txthttps://www.hyperscience.com/llms.txt

How to defend

Double down on vertical-specific workflows where regulatory liability is non-negotiable (insurance underwriting, mortgage processing, healthcare claims) and make the human review loop and audit trail the product, not the extraction. Build proprietary datasets from customer documents that train better models than public data, and license that capability back to customers as a defensible service layer.

  • Ship an MCP server and list it on Stork — biggest single point gain (+25).
  • Get listed in the Anthropic MCP registry, Cursor, or Claude Desktop (+20).
  • Add a usage-based or per-call tier; per-seat-only pricing dies when agents replace seats (+15).
  • Expose API-key auth with a self-serve sandbox tier; remove sales-call gates (+15).
  • Publish an OpenAPI spec at /openapi.json or /.well-known/openapi (+10).

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overview

Overview

Hyperscience focuses on Automation → Document AI → Analyze workflows.

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