Legacy Application Modernization
Takes aging systems that still run the business and moves them to a supportable cloud ready form without breaking the workflows and integrations they carry so the estate stops accumulating risk and cost.
Everything included under this practice line.
Legacy portfolio assessment scoring each application on business value technical health and modernization fit
Rehost replatform refactor rearchitect and replace decisions with cost and risk trade offs documented
Mainframe and midrange offload including COBOL RPG and PL/1 code analysis and conversion
Monolith decomposition into services with strangler fig patterns and anti corruption layers
Database modernization from Oracle DB2 and SQL Server toward PostgreSQL Aurora and managed cloud engines
Integration untangling: replacing point to point interfaces with API and event based patterns
Automated regression suites and shadow traffic testing to protect behavior during cutover
Decommissioning plan for the old stack including data retention and audit continuity
The stack we reach for.
What the business gets, measured.
- Lower total cost of ownership by retiring mainframe MIPS charges and specialist support contracts
- Reduced audit and compliance exposure from unsupported operating systems and runtimes
- Faster feature delivery on systems that previously took heavy change windows to touch
- Access to a wider engineering talent pool by moving off scarce legacy skills
- Resilience improvements from horizontal scaling and cloud native failover
The specialists behind this practice line.
Modernization architects lead the pattern selection and cutover design backed by mainframe engineers Java or .NET refactoring specialists and database migration engineers based on the source stack. QA automation engineers build the parity harness so behavior is provable not assumed.
Compose several capabilities into one engagement.
Digital Transformation Consulting
We sit with your teams map the current stack and workflows and figure out what's actually worth changing. The output is a prioritized backlog not a 90-slide deck.
Cloud Transformation
Lift-and-shift where it makes sense refactor where it doesn't. We move workloads to AWS Azure or GCP with landing zones IaC and a FinOps setup so the bill doesn't surprise anyone.
Enterprise Process Automation
We automate the boring stuff. RPA for the screen-scraping cases proper API integrations everywhere else and workflow engines for anything with approvals or state.
AI-Driven Business Transformation
We embed ML and LLM capabilities into workflows that already exist so ops teams get faster instead of retrained. Starts with one measurable use case not a platform buildout.
Technology Strategy & Roadmap
A 3 year plan that names the systems the sequencing and who owns each bet. We work backwards from business outcomes and cut anything that doesn't move a number.
Digital Product Engineering
We build the customer-facing web and mobile products that carry the transformation story. Cross-functional squads CI/CD from day one and instrumentation before launch.
Business Process Optimization
We instrument the process find where time and money actually leak then fix it. Usually that's fewer handoffs and better data not more software.
Let's talk
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