A stronger foundation
Move runtimes, frameworks, dependencies, and platforms forward through bounded campaigns with a clear target and a verifiable result.
We modernize legacy software without losing the business logic inside it. Understand the system, make a bounded change, and prove it works.
Understand the dependencies before touching the code. The business logic stays at the center.
Isolate one change. Define its boundary while the surrounding system stays intact.
Verify the change against the agreed behavior. Integrate it only when the evidence is there.
Or select a module in the diagram.
Explore a system map, a scoped change, and its verification report. This worked example uses a fictional commerce system, so you can see exactly what delivery looks like.
Payment contractCP-017 · changing
Reads the contract
Indirect dependency
Every fact links to its evidence: a source file, a test, or a runtime trace. Hypotheses are marked as hypotheses.
| Check | Result | Detail |
|---|---|---|
| Contract tests | Passed | 128 of 128 |
| Refund replay | Passed | 2,340 recorded cases · 0 behavior differences |
| Idempotency | Passed | Repeated requests produce one external effect |
| Settlement reconciliation | Not run | Scheduled after every consumer has migrated |
| Known baseline failures | Unchanged | 3 known, tracked separately, not counted as regressions |
A skipped check is never reported as passed.
You don't have to replace the whole system. We start from the outcome you need and choose the smallest useful change. Larger transformations happen in stages.
Move runtimes, frameworks, dependencies, and platforms forward through bounded campaigns with a clear target and a verifiable result.
Untangle business logic, reshape coupled modules, and add new capabilities while preserving the behavior your customers rely on.
Introduce agents into a disciplined engineering workflow your team owns: connected context, isolated execution, and independent verification.
We classify every request by risk and evidence, not just by language, and agree up front on what proves it worked.
Language runtimes, frameworks, SDKs, and build tooling.
Proven by compatibility, a supported target runtime, preserved behavior, and deployable artifacts.
Example A framework upgrade may change date parsing or error handling even when the build passes. We check representative inputs and outputs around the affected behavior.
Bring the current build, a target version, known failures, and an owner who can judge the critical workflows.
Shared libraries, endpoints, events, schemas, and internal clients.
Proven by a complete map of consumers and preserved semantics.
Example Changing a payment value affects every reader, not only the endpoint that writes it. We trace consumers, document the intended semantics, and check each affected boundary.
Bring the contract, known clients, representative payloads, and the domain owner for disputed behavior.
Hosting, authentication, storage, messaging, and observability.
Proven by target operational behavior, failure modes, deployment, and recovery.
Example Moving a service to new hosting can change authentication, retries, or message delivery. A deployable artifact is checked alongside operational behavior and recovery.
Bring deployment access, operational constraints, recovery expectations, and the person responsible for release.
Module extraction, coupling reduction, and subsystem replacement.
Proven by business boundaries, cross-component contracts, and transaction semantics.
Example Extracting billing from a shared module changes ownership and transaction boundaries. We agree on those boundaries before moving code and check the surrounding workflows afterward.
Bring the next business outcome, module owners, transaction rules, and examples of current behavior.
PL/SQL, COBOL, or other legacy logic moved to an approved target.
Proven by preserved business rules and side-by-side behavioral comparison.
Example Rewriting a calculation in a new language can preserve the formula while changing rounding or overflow. Recorded cases and explicit business decisions guide the comparison.
Bring representative inputs, expected outputs, business-rule owners, and a permitted target language.
Schema transformation, database replacement, and ownership changes.
Proven by reconciliation, consistency, cutover, and recovery.
Example Replacing a database involves more than copying rows. We check meaning, relationships, totals, and the point at which reads and writes move to the new system.
Bring data ownership, reconciliation rules, cutover constraints, and the recovery conditions your team requires.
Bug fixes, small features, focused refactoring, and security remediation.
Proven by explicit intended changes, regression checks, and bounded scope.
Example A small refund fix still needs a boundary: repeated requests, authorization, and ledger effects may be involved. We prove the intended change and check nearby regressions.
Bring a reproducible case, the desired behavior, affected users, and an accountable reviewer.
Sometimes the right answer is to retire a system rather than modernize it. We'll tell you when it is.
AI makes writing code cheap. Knowing what a change touches, and proving the system still behaves, is the real work.
Map modules, behavior, and dependencies. Separate what we know from what still needs proof.
Codebase PassportAgree on scope, the behavior to preserve, authorized differences, and how acceptance will be judged.
Transformation contractEach work unit runs in its own sandbox and branch. Agents never deploy or write to protected branches, and impacts on other work are traced.
Reviewable changeAcceptance is checked independently of whoever made the change. Decisions, diffs, and releases are recorded end to end.
Verification reportEach stands on its own. Begin with Discovery, then expand once the first delivery has proven itself.
Executable readiness
Teams that need a credible starting point or a modernization decision.
Repository and build access, an application owner, existing documentation, and known incidents.
Another engineer can run the baseline, see the existing failures, and understand exactly what a successful first change means.
Bounded campaign
A recurring change across one or more applications: a runtime upgrade, an API migration, a platform move.
A sponsor and domain owner, repository and CI access, reviewers for acceptance, and representative test data.
The agreed changes reach production with verification evidence, and every declared exception is resolved or listed.
Delivery program
Organizations running modernization as an ongoing program across maintenance, features, and upgrades.
Portfolio priorities, a budget, an accountable owner for each application, and release ownership.
Reviewed each period: accepted outcomes, cost, and quality against the objectives agreed for that period.
Timelines are set after Discovery, once the real state of the system is known. Data handling, model use, retention, and intellectual property are agreed in writing before work begins.
AI moves fast. Accountability stays human.
We bring AI into a disciplined engineering process: understand the system, agree on the change, and verify the result. Your team keeps ownership of the code, the decisions, and the release.
From the first conversation, you know who is accountable for the result.
Tell us about your system and what needs to change. Prepare your message, then open it in your email app to review and send.
Prepare a project brief first. It's created in your browser, so you can share it with your team, or send it to us when you're ready.