Legacy Modernization
Production-grade Legacy Modernization delivered by senior engineers.
Update and transform legacy systems
- Senior pod
- Real ownership
- Short cycles
- Auditable
- 0+Projects shipped
- 0%Success rate
- 4.9/5Client rating
- 0+Industries served
A senior pod focused on the outcome you need.
Update and transform legacy systems
We embed with your team, run short cycles, and ship working software. Legacy Modernization is a discipline we own end to end - from architecture through production support.
- Production-grade implementationTested, observable, deployed.
- A measurable outcomeMetrics agreed up front, evidence at the end.
- Knowledge your team ownsArchitecture docs, runbooks, on-call training.
What you get when we engage.
Each engagement covers these capabilities by default. We tune the mix to your problem instead of selling a fixed package.
- 01
Architecture & design
End-to-end legacy modernization architecture sized to your problem, not a template.
- Clear blueprint
- Risk surfaced early
- Cost transparent
- 02
Production delivery
We ship, not slides. Tests, observability and deployment are built in from week one.
- Working software
- Tested code
- Real telemetry
- 03
Operate & evolve
After launch we stay close, hardening the system and helping the team own it confidently.
- Knowledge transfer
- Support cadence
- Iterative improvements
Three layers. One spine. Tuned to your stack.
Every legacy modernization engagement we ship sits on the same spine: a clean separation between the source systems, the intelligence layer and the surfaces your operators actually use. We adapt each layer to your stack, governance and delivery model, not the other way around.
- Source of truthYour existing systems, datasets and event streams stay authoritative. We integrate cleanly, we do not force a migration.
- Intelligence & orchestrationModels, rules, workflows and controls turn raw data into decisions your teams can inspect and improve.
- Operator surfacesDashboards, APIs and workflow tools are built for the people using the system every day, not for a demo.
- Ingest
- Models & rules
- Observability
What changes after we ship.
Measurable signals from recent legacy modernization engagements. Yours will be specific to your baseline - agreed before we start, evidenced at the end.
- 0%Faster time-to-productionAverage across recent engagements.
- 0%Fewer production incidentsAfter our hardening cycle.
- 0×Higher engineering throughputBy the end of quarter one.
- 0%Auditable by designEvery decision logged and reviewable.
Ship in weeks. Learn in days. Compound forever.
A lean operating model built for the AI era - discovery, MVP, production, evolution. We work in two-week loops with embedded GenAI tooling, instrument outcomes from sprint one, and hand over a system your team genuinely owns.
- Phase 011-2 weeks
Discover & frame
Translate the business outcome into a sharp hypothesis. Map constraints, surface risk, and pick the one slice worth proving first.
Deliverables- Outcome brief
- Risk register
- Feasibility cut
- Phase 021-3 weeks
Prototype & validate
Ship the thinnest viable slice end-to-end. Real data, real users, AI-assisted tooling - proves the bet before we scale the team.
Deliverables- Working prototype
- Eval harness
- Decision log
- Phase 034-12 weeks
Build & instrument
Senior pods deliver production-grade code in two-week loops. SLOs, traces and observability ship with the first release, not the last.
Deliverables- Working software each sprint
- SLOs + tracing
- Test coverage
- Phase 04Ongoing
Operate & evolve
Stay close after launch. Runbooks, retraining cadences and a quarterly outcome review - so the system keeps compounding, not decaying.
Deliverables- Runbooks + on-call
- Retraining cadence
- Quarterly outcome review
Built for the worst hour, not the demo hour.
Legacy Modernization engagements ship into environments where uptime, auditability and clear human override matter on day one. Every system we build assumes someone will get paged at 2am - and prepares for it.
- Observable from minute oneTracing, metrics and structured logs ship with the first slice.
- Safety boundaries by defaultFailure modes simulated and bounded before features get added.
- Operators in the roomWe design with the people who'll run the system, not at them.
What we build with.
We pick tools for fit, not familiarity. Most engagements stay close to the stack you already run, with deliberate additions where they earn it.
- TypeScript
- Python
- Go
- PostgreSQL
- Redis
Common questions.
Don't see yours? Just ask.
- Most engagements start with a 1-2 week discovery, then run as embedded squads in two-week sprints with a senior partner overseeing delivery from kickoff to handover.
- Production-shaped slices typically land within 4-6 weeks. We optimise for visible progress over big-bang releases.
- Yes. Most clients keep us on a smaller cadence after launch for hardening, support, and the next iteration of work.
Ready to talk about Legacy Modernization?
Send us a brief. A senior engineer reads every one and replies within one business day, with an honest read on whether we're the right fit.
- Reply in 1 business day
- NDA on request
- Senior engineer, not sales