Modernizer · The code modernization layer

Make legacy code
agent‑ready.

The Kubernetes-native engine that prepares enterprise legacy codebases for autonomous AI agents — documented, tested, modular, and safe to change.

Book a demo → Watch the film

MONOLITH

The problem

One monolith. Inside — a knot of hidden dependencies. One small change, and everything reacts.

The world's enterprise code is unprepared for AI.

$0T

Drained annually from the US economy by technical debt.

Of core IT budgets lost maintaining fragile legacy code.

∞

Hallucination loops — agent fleets burning enterprise tokens on code they can't parse.

From legacy code to modern software.

Modernizer fixes the foundation before you hire an AI workforce. Background agent pipelines run inside your own cloud VPC and systematically upgrade legacy repositories — for LLM context windows and human teams alike.

Automated reverse‑engineering

Maps undocumented dependencies and builds clean, machine-readable system documentation.

The agent safety net

Generates 80%+ behavior-validation characterization tests to guarantee zero-regression refactoring.

Context optimization

Restructures monoliths into modular, strictly-typed files agents parse without choking on token limits.

How it works

Understand

Modernizer maps your entire system — components, dependencies, data flows, APIs, and the hidden relationships nobody documented.

Design

It plans the modernization path — what stays, what moves, what becomes a service, and what must be tested first. A human approves every decision.

Build

Then it builds — services, APIs, tests, infrastructure and deployment pipelines. The monolith becomes microservices.

Run

Production-ready software, deployed to your cloud. In one project: a ~1M-line monolith, decomposed and running on AWS.

The film

76 seconds. The whole story.

The engine

One controlled process.

Modernizer runs on an AI software factory engine — autonomous where it's safe, human-approved where it matters.

Graph memory

A living map of the whole system, not a context window snapshot.

Multiple models

The right model for each task — analysis, planning, generation, review.

Enterprise tools

Git, CI/CD, ticketing and cloud — clean versioning, deterministic pipelines.

Human approval

Every architectural decision gates on a human. No silent rewrites.

The outcome

Not a report.
Production‑ready software.

Modern software your team can run, test, deploy, and keep improving — in your cloud, under your process.

Services, APIs and strict typing — agent-parsable by design
80%+ characterization-test coverage as the safety net
Infrastructure and deployment pipelines included
Proven at ~1M lines of code — monolith → microservices on AWS

modernized-app — deploy

$ npm test

✓ 247 passing · 84% coverage

$ git push origin main

✓ build · type-check · characterization tests

$ deploy → aws

✓ monolith → microservices

production · running on AWS

Get your Agent‑Friendliness Score.

A fast-tracked diagnostic maps your repository's complexity and scores exactly how ready it is for an autonomous AI workforce — and what it takes to get there.

Make legacy codeagent‑ready.