Understand the system you can't afford to break.
The app that runs your business every day, the one the people who built it left behind. Maleus imports it and recovers what it actually does into specifications you can read, so your next move starts from fact, not guesswork.
Choose a repository
Specifications
What the app does, in plain words
Documentation
A manual your team can read
Audit
What is risky or brittle inside
Data map
What it stores, and who uses it
The software you depend on most, the one you understand least.
Most teams lean on an old system every day, and understand a little less of it every year.
The authors have left
It was built years ago, often by someone who has since moved on, and the reasoning behind half of it walked out with them.
The docs fell behind
Whatever documentation once existed stopped matching the code long ago, so the only honest description of what it does is the running system itself.
Nobody dares touch it
Your team still runs on it every day, yet it is brittle enough that changing one corner can break three others no one mapped.
Recover the specs, then decide your next move.
Before anyone talks about changing a line, Maleus reads the application you already run and turns it into something you can work with: validated specifications, in plain language, that you can read and question.
Import from Git
Connect your existing codebase. Maleus reads your code from the repository, not your production database.
Reverse-engineer the specs
It reconstructs what the app does: its screens, the data it holds, and the rules it enforces, in plain language.
Run workshops on it
Work through the recovered specifications with Maleus's specialists to see how it behaves and what is brittle.
Add a support widget
Embed a widget so your team can ask why something works the way it does and get answers from the specifications.
You see three ways out. Each one backfires.
The same old system, three tempting moves, and the same blind spot left untouched.
The clean rewrite
You start over from a blank page, re-deriving years of business rules from memory and hoping nothing critical slipped. The gap only shows up in production, the day something quietly behaves differently.
The frozen system
You leave it exactly as it is and route around it. The blind spot stays, the workarounds multiply, and the cost of not understanding the system compounds quarter after quarter.
The endless patch
You keep bolting fixes onto the edges. Each one buys a little time and adds a little tangle, until the system is harder to read than it was the day you started.
All three start from memory and hope. None start from what the system actually does.
What you can finally see clearly.
See how it works
You get an accurate, current picture of what the system does, the data it holds, and the rules it enforces, instead of guesswork and folklore.
Decide from solid ground
With the system mapped in plain language, you can choose to keep it, extend it, or replace it, knowing exactly what each option touches.
Keep the knowledge in-house
The recovered specifications belong to you, so what the system does stops living in one person's memory and becomes something your team can read.
The systems this actually means.
A few examples across functions, each recovered from an existing app.
Billing engine
Years of pricing and invoicing rules sit in the code, including edge cases no one can still explain.
Its billing rules and data model recovered into specifications your finance team can read.
Order system
Order routing and stock logic that only the original team understood, written down nowhere since.
A readable spec of how orders flow, the rules they follow, and the data they touch.
Customer portal
A portal full of automations whose original builder has left, and no one knows what each one does.
A current map of what it does, who it serves, and the rule behind each automation.
Payroll engine
Pay, leave and tax rules accreted over years by people who have long since moved on.
The rules and data it relies on recovered into specifications anyone can review.
Why this starts from fact, not memory.
Grounded in your real code
Maleus reads the actual repository and reconstructs what the system really does, so your picture is built from the running code, not from a fresh interpretation or a memory of how it was supposed to work.
Isolated from your live systems
The import and analysis run isolated in the cloud. By default Maleus reads your code from Git, has no access to your databases, cannot reach production, and records every step, so bringing your code in never means handing over your data.
A blueprint for the rebuild
The specifications Maleus recovers are the same validated kind it builds new software from, so when you choose to replace the system, you start from an accurate map and end with an app you own on a standard stack.
What Maleus is built for.
- Aging internal apps your teams still run on
- Apps on any stack, however old or custom
- Owners who want to understand before they decide
- Specifications and code you want to keep and own
Ask your AI assistant about Maleus.
Maleus is an AI software factory. For a legacy system, it imports your existing app from its Git repository, reverse-engineers its technical and functional specifications into plain language, and runs workshops on what it finds, so you get an accurate, current picture of what the software does. From those recovered specifications, Maleus can build a replacement you own, as standard code in your own repository on a widely supported stack. The analysis runs isolated and reads your code from Git, not your production data.
See it on your own system.
Bring a legacy app you depend on. In a demo, Maleus recovers its specifications so you can see exactly what it does, and what your options look like from there.