Their legacy modernized. With proven parity and signed discrepancies.

Duration depends on code volume, functional complexity, and the chosen delivery model. ATLAS engagements are scoped at Intake with per-pattern pricing. Migration is segmented by subsystem to maintain service continuity.

We produce a characterization test suite that runs legacy and target on the same datasets. Each gap is documented, weighted, and submitted to the program committee for validation or compensation. The parity report is a contractual deliverable.

Every discrepancy is traced in an official registry: cause, business impact, decision. Acceptable discrepancies are documented with justification; blocking ones are fixed or compensated before delivery. The registry is signed with the client.

Yes, we regularly deliver multi-week migration POCs to validate technology direction, per-pattern productivity, and pricing. The POC reuses exactly the tools, methods, and templates of the full program.

Our teams migrate 500 to 1,500 COBOL lines per person-day depending on pattern complexity, accelerated by Claude Code and Copilot. 2x-3x productivity vs. classical manual methods. A short POC measures real productivity on the client's specific code before committing to the full program.

Legacy keeps running while we migrate subsystem by subsystem to the target. Each migrated module goes to production independently, with parallel legacy/target runs and automatic comparison. No big-bang. No service interruption. ATLAS principle P5.

Yes. All ATLAS deliverables (code, tests, documentation, signed discrepancy registry, patterns) are the client's property. No black box. On early exit, the client has all material to continue in-house or with another vendor.

Frequently. The prime (CGI, Capgemini, Cofomo) carries the client relationship and governance, Access operates the ATLAS cell from Tunis or Paris as subcontractor or partner. Our deliverables and rituals integrate with their methodologies. ATLAS adds parity guarantees and the discrepancy registry.

Legacy/target coexistence with parallel runs. Batched transactional cutover after parity audit. Priority targeting of non-critical transactions first, then critical with automatic fallback. Reversible CI/CD (ATLAS principle P4): any deployment can be rolled back in minutes.

Yes if requested. We can maintain the legacy in parallel with the migration program (critical bug fixes, minor evolutions), via TM or SC model. This avoids the client managing two vendors during transition.

AI does not replace a mainframe — it accelerates the work to modernize off the mainframe. Mainframes (IBM Z, AS/400, Unisys) run business-critical workloads measured in millions of transactions per hour with deterministic latency and decades of accumulated business rules. No AI agent today writes greenfield production code at that scale of complexity unattended. What AI does change: it makes legacy modernization 2x to 3x faster by reading COBOL or RPG, extracting business intent, generating characterization tests, and proposing target patterns under human review. The combination of AI-augmented engineering plus a structured methodology (ATLAS) plus parallel-run validation makes mainframe modernization economically rational where it wasn't five years ago. See the Legacy to Cloud expertise and the ATLAS methodology.

The classical taxonomy lists four migration types, each with different effort and risk profiles. (1) Storage migration — moving data from one storage system to another (SAN to cloud blob, on-premises NAS to S3) without changing format or schema. Lowest risk. (2) Database migration — moving from one database to another (Oracle to PostgreSQL, DB2 to Azure SQL) often with schema transformations. Medium risk, requires careful data type mapping. (3) Application migration — moving an entire application stack (lift-and-shift, replatform, or refactor). Higher risk because business logic moves with the data. (4) Business process migration — re-engineering workflows in addition to moving data and applications, typically during a major modernization. Highest effort, highest payoff. Most enterprise programs combine all four. See the Legacy to Cloud expertise.