Dependency mapping
Automated scanners map undocumented logic, data flows, and integrations before any refactoring begins.
Proof layer You get a dependency map and architecture assessment a procurement or security review can read.
Legacy and modern run side by side, outputs compared, then cut over one increment at a time.
What we built
Mapping, parallel running, mirrored verification, and incremental cutover. Each step is proven before the next one starts, and every one can be rolled back.
Automated scanners map undocumented logic, data flows, and integrations before any refactoring begins.
Proof layer You get a dependency map and architecture assessment a procurement or security review can read.
A modern environment runs beside the legacy core so daily operations never stop.
Proof layer The legacy system stays the system of record until the modern path clears its parity threshold.
The same traffic flows through both systems and every output is compared programmatically for parity.
Proof layer Nothing cuts over until the diff report is clean on real production traffic, not test fixtures.
We modernize component by component, never in one risky rewrite.
Proof layer Each increment has a written rollback path, so any step can be reversed inside a maintenance window.
Use cases
If it is critical, undocumented, and nobody wants to be the one who touches it, it is a candidate. These are the shapes we see most.
Wraps the monolith in modern APIs, then peels off one bounded domain at a time while the monolith keeps serving the rest.
SaaS · Retail · LogisticsMoves DB2, Oracle, or SQL Server workloads to PostgreSQL or managed cloud with dual writes and row-level reconciliation.
Finance · Healthcare · Public sectorExposes mainframe transactions through a modern API layer so new products ship without touching the core until it is ready.
State & county · Insurance · BankingContainerizes workloads, replaces hand-managed servers with Kubernetes, and cuts over environment by environment.
Manufacturing · Education · NonprofitsReplaces spreadsheets and disconnected admin tools with one role-based internal system that owns the data.
E-commerce · Operations · Field serviceReplaces brittle point-to-point scripts and nightly batch jobs with event-driven integrations you can observe.
ERP · CRM · 3PLProfiles the slow paths, fixes queries, caching, and hot loops, and proves the gain against the original baseline.
High-traffic apps · Portals · ReportingMoves off unsupported frameworks and runtimes with a documented change log an auditor or prime can review.
Healthcare · Government · Regulated SaaSClient stories
Each one replaced something fragile that a team depended on every day. Each one went live without a stop-the-world rewrite.
How we ship
Every modernization leaves with the same four things defined in the plan before a line of legacy code is touched.
Production requires proving it on real traffic, every day, until cutover.
We assume something will surprise us and plan the reverse path first.
Modernization changes the system everyone depends on, so the record has to be readable by non-engineers.
Parallel running is temporary by design, and the plan says when it ends.
WHO RUNS IT AFTER CUTOVER
WHAT WE WILL NOT BUILD
For SLED scope under NAICS 541512, we untangle mainframe and legacy technical debt as your subcontractor, working behind the prime, never facing the agency.
NDA-first, subcontract-only. We work behind the prime, under your brand. We do not pursue prime contracts and we never face the agency.
Verified and reversible. Mirrored traffic proves parity before cutover, and every increment can be rolled back.
Built for security review. Architecture assessments, dependency maps, and zero-downtime strategies a procurement review can read.
FAQ
Straight answers about retiring legacy without the rewrite risk. If yours isn't here, ask it on the call, we answer the hard ones first.
Ask the hard oneNo. We use parallel running environments to ensure zero downtime during the cutover process.
We use automated dependency scanners to map the logic and architecture before any refactoring begins.
We strongly advise against a full rewrite. We modernize incrementally, component by component.
We run mirrored traffic through both systems simultaneously and compare the outputs programmatically to ensure perfect parity.
A fair instinct. The danger is doing it under pressure later. We de-risk it with parallel environments and incremental, mathematically verified, fully reversible cutovers.
Start the conversation
Tell us which old system everyone is afraid to touch. That is where we start mapping.