Enterprise Business Logic Extraction & Governance Platform

The pain is real: enterprises lose years trying to reverse-engineer business logic from fragmented legacy systems before modernization. Rhino's approach of extracting logic from code, SaaS configs, and documents into a governed graph (UAN) is a genuine gap — existing tools stop at code or focus on process mining. The hard part is trust: enterprises must trust the extraction accuracy and the governance model. Distribution requires enterprise sales cycles and proof points. For this to work, Rhino must land a lighthouse customer with a painful legacy migration and deliver measurable time savings.

Enterprises spend billions on legacy modernization but lack tools to extract business logic holistically. Existing tools (CAST, Blueprint) focus on code analysis, ignoring SaaS configs and documents. AI agents need structured business logic to avoid brittle, hard-coded prompts.

Enterprises struggle to document business logic from legacy systems. Existing tools focus on code analysis, ignoring SaaS configs and documents. AI agents require structured business logic to avoid brittle prompts.

Large TAM, urgent need, AI tailwind Lost logic causes project failures

Heuristic scoring based on model judgment, not factual measurement.

LLMs enable extraction from documents CIOs prioritize modernization post-COVID No unified extraction+governance platform

The market timing is favorable due to technology enablement (AI) and strong demand signals from enterprises undergoing legacy modernization. However, distribution remains challenging for a bootstrapped founder, and regulatory tailwinds are weak. The window is open but requires rapid validation.