How It Works 3 min read

How Catalio Works

Understand the Extract, Understand, and Evolve workflow that turns undocumented systems into living specifications

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Decades of business logic are trapped in systems nobody fully understands. Engineers who built core systems retired – their knowledge went with them. Modernization projects stall because no one can map what the system actually does.

Catalio solves this with a three-phase approach: Extract, Understand, and Evolve.

The Three Phases

Phase 1: Extract

Catalio connects to your platforms and surfaces every business rule, process, and dependency automatically. Whether it’s a legacy ERP written in COBOL, a heavily customized Salesforce org, or an internal tool built over 15 years of patches – Catalio pulls in the full picture.

What gets extracted:

  • Components: Fields, endpoints, rules, objects, UI elements with full metadata
  • Business rules: Validation logic, workflow automations, calculated fields
  • Dependencies: How components relate to and depend on each other
  • Processes: End-to-end workflows and their decision points

Tip

You can connect via repository, API, or metadata export – whatever your system supports.

Phase 2: Understand

Once extracted, every component gets AI-enriched with summaries and semantic tags – searchable by purpose, not just name. The result is a living specification: a complete picture of what your system does today.

This isn’t a static document that goes stale the moment it’s written. The living specification:

  • Updates as your system changes
  • Organizes business logic into features, requirements, and acceptance criteria
  • Provides a real-time PRD for your entire application
  • Makes institutional knowledge searchable and shareable

Phase 3: Evolve

With a complete understanding of your current state, you can plan and deliver changes with full context. Catalio’s AI performs gap analysis on every initiative – comparing what exists today against where you want to go.

For modernization projects:

  • Map legacy business rules to target architecture components
  • Identify gaps before they become production issues
  • Trace every requirement through implementation
  • Keep the specification current as you ship changes

The Six-Step Process

Here’s what the workflow looks like in practice:

  1. Connect your application – Link your legacy system, custom platform, or business SaaS
  2. Sync components – Pull in every building block with full metadata
  3. AI enrichment – Every component gets an AI summary and semantic tags
  4. Extract requirements – Reverse-engineer features, requirements, and policies from your enriched inventory
  5. Living dashboard – Your application becomes a real-time specification
  6. Create initiatives – Plan changes against the living spec with AI gap-analysis

Key Results

Teams using Catalio report:

  • 40% faster migrations – start from a complete, verified picture instead of guesswork
  • 90% AI code generation accuracy – AI tools get the business rules they need
  • 100% rule preservation – gap analysis ensures nothing slips through
  • Zero knowledge lost – institutional knowledge is captured and searchable

What’s Next?

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