ATLAS. The framework that makes legacy modernization predictable.

ATLAS is Access International's operational framework for modernizing legacy applications with proven parity. It structures the program around ten steps, nine guiding principles, and six team poles. It covers three legacy families: COBOL, Delphi, and BizTalk-type middleware.

ATLAS enforces functional parity before any redesign: target code must first reproduce legacy behavior exactly, measured by characterization tests written upstream. Discrepancies are traced in an official registry, weighted, and validated or compensated before go-live.

ATLAS covers three families: COBOL (z/OS mainframe, AS/400, Unisys) to Java, .NET Core, TypeScript or Python; Delphi and 4GL environments to .NET Core or TypeScript; BizTalk middleware and modern mainframe to Azure Logic Apps or AWS.

Duration depends on code volume, functional complexity, and the chosen delivery model (TM, RC, CC, or SC). Every program is scoped at Intake with per-pattern budgeting and a subsystem-by-subsystem delivery plan.

We do not publish rate cards. Pricing is built at Intake from code volume, functional complexity, delivery model, and target parity level. A short multi-week POC measures real per-pattern productivity before committing to the full program, yielding a multi-year quote based on measurements, not assumptions.

Every ATLAS program is delivered with exhaustive documentation, a signed discrepancy registry, and a transferred automated test suite. Migrated patterns and tooling are the client's property. On exit, the client has enough material to continue in-house or with another vendor — no black box.

Knowledge transfer is planned from Discovery. Concretely: systematic pair-programming on recurring patterns, shared code reviews, a documented pattern library, monthly workshops with client teams. At delivery, the client has an autonomous internal team on the delivered foundation.

Yes. The strangler fig strategy migrates subsystem by subsystem while the rest of the legacy keeps running. Each migrated module goes to production independently, with parallel legacy/target runs. No client is forced into a big-bang.

A short POC (Intake + Discovery + migration of a representative subsystem) is billed at direct cost (a few cell-weeks). It rolls into the overall scoping if the program proceeds. If stopped, the client keeps the POC deliverables and can reuse them.

Yes. We frequently operate in co-delivery: the prime carries the client relationship, governance, and contractual liability; Access operates the ATLAS cell as subcontractor or partner. Deliverables, rituals, and tooling stay consistent with the prime's methodology, with ATLAS layered on top.

Every discrepancy identified between legacy and target is traced in an official registry with: nature, business impact, proposed resolution or compensation. The program committee (client + Access) arbitrates and signs the registry. Acceptable discrepancies are documented; blocking ones are fixed before production.

The characterization test suite delivered at parity validation covers the vast majority of business behaviors. Any regression detected in production beyond the tested scope is jointly analyzed: if outside the registry's coverage, it is handled as evolutionary maintenance; if inside the guaranteed perimeter, it is fixed under SLA.

The ATLAS methodology structures every legacy modernization in 10 phases with kill/go gates between each. E1 Intake — scope, constraints, success criteria. E2 Discovery — deep code analysis, business intent mapping. E2b Functional spec — readable analysis from the existing code. E2e Existing-state capture — frozen reference of truth. E3 Dependency mapping — exhaustive system interaction graph. E4 Target architecture — technology mapping, ADR. E4b Pre-migration tests — characterization suite written before any target code. E5 Migration — pattern-by-pattern translation with line-level traceability. E6 Parity validation — proof of functional equivalence on real datasets. E7 Delivery — cutover, documentation, internal classified discrepancy registry. The framework adapts to client governance (Scrum, SAFe, PRINCE2). See the ATLAS methodology for the full operational playbook.

Yes, to recover the business rules. The compiled program is decompiled with Ghidra, then the names of published methods and fields are rebuilt from the program's internal tables; private methods are identified by their calculation. Each rule is proven by its address in the binary, its instructions and its constants. On our internal POC Raptor Invoice, an open-source Delphi application, the invoice line calculation, the total with reminder fees and the late-interest formula were recovered from the executable alone. Feasibility depends on the technology and is assessed at the Intake step. See the Raptor Invoice migration.

Because a migration faithful to the source is only faithful to production if that source is really the one that was compiled. A version patched in a hurry may never have been archived. ATLAS checks, function by function, the rules extracted from the executable against those of the source provided, and any gap is logged in the discrepancy registry. On the internal POC Raptor Invoice, the five functions compared matched.

The strangler-fig pattern (named after the strangler fig tree, which slowly grows around a host tree until the host is no longer needed) is the default ATLAS approach to legacy modernization. Instead of a big-bang rewrite, sub-systems migrate one at a time: a new module is built, tested, deployed, and traffic is rerouted from the legacy to the new system, while the rest of the legacy keeps running. After enough iterations, the legacy is fully replaced — but the program never has a single high-risk cutover moment. The advantages: any sub-system delivered enters production independently, kill/go gates between modules let you pause without losing work, and parallel runs validate parity on real production traffic before final cutover. The strangler-fig approach is principle 5 of the ATLAS methodology. See the ATLAS methodology for the operational details.