Technical debt, rebalanced

Convert legacy codebases into AI-ready specs. Make informed decisions, reduce delivery risk, and shift spend to innovation.

Why modernization projects struggle

Legacy systems hide coupling and impact. Teams waste time tracing what breaks when they change code, and delivery slows down.

Outdated stacks and undocumented APIs create risk. Security reviews happen too late, and compliance becomes a bottleneck.

Automation is built on guesswork without a clear spec. Duplicate effort, wrong priorities, and tools that don’t match reality.

Three steps from legacy code to actionable specs. Emphasize AI-ready specifications output.

Step 1

Import and map your codebase. Get a clear picture of structure, dependencies, and tech stack.

Step 2

Run security, features, and impact analysis. Identify risks and opportunities with AI-assisted insights.

Step 3

Produce AI-ready specifications—EARS, BDD, or your format. Use them to drive decisions and automation.

After a merger or acquisition, quickly understand inherited systems, rationalize stacks, and plan a unified roadmap with AI-ready specs.

Turn ageing monoliths into documented, spec-driven targets. Reduce risk and align teams on what to change and in what order.

Map dependencies and impacts before you move. Generate specs that support lift-and-shift decisions and refactor priorities.

Give new joiners and teams a clear map of the codebase. Use specs to accelerate onboarding and reduce tribal knowledge.

Start your analysis and turn legacy code into AI-ready specifications.