Legacy Lifter
- Legacy Lifter
Read the Entire Estate Before You Commit to a Plan
Legacy Lifter turns deployed code into a specification you can build against and test against. Every rule traces back to the line it came from, so the rebuilt system is checked against the one it replaces, not against requirements someone remembered. The record regenerates as the code changes, so the understanding does not go stale the week after the assessment ships.
Built for the engineering leaders who must sign off on changing a system nobody fully understands.
Your Engineers Read
More Than They Write
58–70%
of developer time goes to understanding code, not writing it
40%
of the average enterprise IT balance sheet is technical debt
20%
more spent on every modernization project just to work through legacy complexity
The tax is not paid once. It is deducted from every sprint, every release, and every modernization business case you will ever write.
Legacy Estates Fail in Six Familiar Ways
Not every legacy estate is in trouble. These six are the tells that yours is.
01
Slow Onboarding
A new engineer waits months before anyone will let them change a core system alone.
02
Guesswork Estimates
Legacy work gets scoped before anyone has read the code that has to change. The overrun is how you find out.
03
Hidden Dependencies
Dependencies surface in the middle of the project, discovered by the change that breaks them.
04
Knowledge Silos
Every safe change to the system that matters most routes through the same two people, and their availability sets your release dates.
05
Documentation Drift
The documentation describes a version of the system that no longer runs.
06
Unread Code
Code enters the repository faster than the team reviews it, and the share nobody has read grows every release.
They’re symptoms of the same thing: the system is no longer fully knowable.
Modernization Plans Built on Memory
Systems get modernized without ever being mapped first, so every team rediscovers the same logic from scratch, one release at a time.
Industry norm
Modernization roadmaps get built on developer interviews, tribal memory, and documentation that stopped being updated years ago.
Institutional knowledge leaves with retiring SMEs, and undocumented systems turn into black boxes nobody wants to own.
Reverse engineering happens once, as a one-time project, then goes stale the moment the next release ships.
“Understanding the application” and “having a modernization roadmap” get treated as the same deliverable.
The Legacy Lifter approach
Walks the actual codebase line by line and builds a complete, traceable map of what the system really does.
Extracts and preserves business logic, dependencies, and intent straight from the code, independent of who is left to explain it.
Converts what it learns into structured specifications that feed directly into spec-driven development and forward engineering.
Treats extraction as the input to modernization, not the finish line.
Purpose-Built Agents Behind One Traceable Record
The agents read different layers of the application, from dependencies to dead code, and bring everything they uncover into one shared, always-current knowledge base. Indium engineers stay involved throughout, so you are not handed a black box and left to work out whether to believe it.
MAP
Dependency Mapper
Traces every connection between modules, functions, and external systems, including the ones nobody documented.
A complete dependency graph, and exactly what breaks if you change something.
RULE
Business Rule Extractor
Reads the code itself and extracts the business logic embedded inside it, not just the structure around it.
Plain-English documentation of what the system does, rule by rule.
FLOW
Data Flow Analyzer
Maps how data moves through the system from input to output, across every transformation in between.
Visual data flow showing every transformation and touch point.
JOB
Job Dependency Mapper
Finds scheduled jobs, batch processes, and the relationships and timing between them.
Job schedule map with dependencies and timing laid out.
REDUNDANT
Dead Code Finder
Identifies code that is no longer executed or referenced anywhere in the system.
A candidate list for retirement, with the evidence behind each call.
DOC
Documentation Extractor
Pulls comments, commit history, and buried context into a single, usable record.
An onboarding guide any engineer joining the system can actually use.
SPEC
Spec Generator
Converts the extracted knowledge, dependencies, and business rules into structured specifications.
Forward-engineering specs, ready for spec-driven development.
Together, these agents turn an undocumented legacy system into a fully traceable, forward-engineering-ready knowledge base.
15x Faster Analysis
40% lower engineering effort across enterprises running Legacy Lifter.
Strengthen Confidence
Every extracted rule and dependency traces back to source, so modernization decisions rest on evidence rather than memory.
Accelerate Discovery
Assessment cycles compress from months to weeks, and roughly a third of developer time comes back from reading old code.
Reduce Technical Debt
Debt hotspots and undocumented logic surface before they inflate modernization cost and timelines.
Empower Teams
Architects and engineers stop doing manual archaeology, and tribal knowledge becomes a shared, current record.
Seven Layers, From Interface to Persistence
For architects and engineering leads evaluating the platform in depth: the full system architecture, and the technologies each layer runs on.
Legacy Lifter Runs on Your Infrastructure
Deployment model
On-premises deployment supported, alongside cloud and hybrid options.
Data handling
Legacy Lifter can run entirely within your own environment using private and open-source models. No code or data needs to leave your control.
Auditability
Every extracted rule, dependency, and specification is reviewable by an Indium engineer before it is acted on.
Indium Engineers Build Against the Spec
The agents produce the specification. These four services are how Indium engineers build against it.
Application Modernization Advisory
Engineers translate the extracted knowledge into a phased, prioritized modernization roadmap.
A plan tied to business risk.
Migration & Re-platforming
Hands-on engineering to execute the move from current stack to target stack, built against the extracted specification rather than against interviews.
A re-platformed application.
SME-in-the-loop Validation
Engineers review and validate every extracted business rule and dependency before it is trusted, and again before it is built on.
A validated, audit-ready knowledge base.
4-week Proof of Value
A scoped pilot that runs Legacy Lifter against a real slice of your system.
A PoV report with a go or no-go call.
Every extracted rule traces back to the line of code it came from, which is what makes equivalence checkable.
Assessing a 4GL Legacy Architecture for a Leading Insurer in 12 Weeks
Deciphering the Logic of 170 Critical PICK BASIC Programs for a North American Retailer
The Lifter Delivers 10x Faster Legacy Discovery for a Large IT Enterprise
See How Legacy Lifter Works
Eliminate the Reverse Engineering Tax in Modernization with Legacy Lifter
Start With Your Most Complex System
Run a four-week Proof of Value against a real slice of it. You walk away with a real dependency map, real business rules, and a real modernization case, not a guess.
What you walk away with
- A complete dependency map
- Business logic documented in plain language
- Structured specifications ready for the forward build
- A go or no-go call, backed by pilot data
Frequently asked questions about Legacy Lifter
1. Can Legacy Lifter help us understand an undocumented legacy system?
Yes. Legacy Lifter uses agentic AI to reverse engineer existing applications and create a complete, traceable knowledge base from the code. This turns system knowledge from something held in people’s heads into something that can be understood, verified, and handed to the next engineer.
2. What if we already have documentation for our legacy application?
Legacy Lifter works from what the system actually does, not just what existing documentation says it should do. Architecture diagrams and documentation can fall behind the code over time. Legacy Lifter extracts system knowledge from the application itself, giving teams a current view of how the system works.
3. Does Legacy Lifter only document legacy applications, or can it support the modernization itself?
It supports both. The agents create a verified specification of how the application works, and Indium engineers use that specification to guide the rebuild. Every rule can be traced back to the source code, giving teams an anchor for validating the modernized application against the original system.
4. How does Legacy Lifter reduce the risk of legacy application modernization?
Legacy Lifter compresses the discovery phase by using agentic AI to extract and structure system knowledge before modernization begins. This helps teams understand what the application actually does before timelines and rebuild decisi4ons are locked in, reducing uncertainty that can derail modernization programs.
5. How does Legacy Lifter keep the knowledge base up to date?
The knowledge base is generated from the application code rather than manually maintained. As the system changes, Legacy Lifter can regenerate the knowledge base so it reflects the application as it exists today, rather than relying on documentation that may have become outdated.
6. How accurate is AI-powered legacy application reverse engineering?
Legacy Lifter provides traceability from extracted rules back to the source code, so teams can verify where each piece of system knowledge came from. An Indium engineer also validates the extracted information before it is trusted for modernization. The result is not a black box. The evidence behind the extraction can be checked.