We help you move from one large, risky release to services each team can deploy on its own. We map where to split, move traffic across a little at a time using the strangler pattern, and send every change through pipelines with security checks.
What's included
6 capabilities, delivered by one squad. Use what you need now and add more as you grow.
Find the natural split points in the code, define service boundaries and extract each service with a clear contract.
Route traffic gradually from the monolith to new services, with a safe way back at every step.
Split the shared database so each service owns its data, using CDC and the outbox pattern to keep data in step during the move.
Replace direct calls between services with events and queues, so one slow service doesn't hold up the others.
Pipelines with security scans, policy checks and a record of every release, so security doesn't slip during the move.
Logs, metrics, traces and SLOs measured before and after each cut-over, so you can see whether it worked.
Our approach
The usual way
So-called microservices that still share database tables and deploy together.
How we do it
Clear service boundaries and API contracts, with each service owning its own database schema.
The usual way
All traffic moves to the new system in one go, so a single fault can take everything down.
How we do it
Strangler routing moves traffic a slice at a time, with monitoring and a way back at every step.
The usual way
Releases depend on manual steps, with no security checks or record of what was shipped.
How we do it
Every release goes through pipelines with policy gates, scans, SBOMs and activity records.
Architecture
Each layer has a clear job, so the system is easier to secure, test and extend.
Service boundaries and API contracts that stop you ending up with a distributed monolith: many services that still change and deploy together.
Strangler routing, feature flags and canary releases move traffic safely while production keeps running.
A separate schema per service, with CDC, the outbox pattern and anti-corruption layers keeping old and new data models apart.
Automated policy checks, secure delivery and activity records, so modernisation doesn't weaken security.
How we deliver
4 phases, each ending with an output you can review.
We map the business areas in your code, the parts most tangled together and every integration point, then agree how to measure success.
Output: Decoupling blueprint
We design strangler routing, feature flags, canaries and rollback plans before any service is extracted.
Output: Safe migration plan
We extract the first services, move their data out with CDC and the outbox pattern, and give each one its own schema.
Output: First independent services
We add policy gates, SBOMs, SLOs and monitoring, then repeat the same steps for the rest of the system.
Output: Repeatable modernisation process
Your team
Specialists join your squad for this work, alongside a delivery lead who keeps you updated.
Maps service boundaries, contracts and extraction order, so each step removes complexity instead of moving it around.
Sets up strangler routing, feature flags, canaries and rollback for safe production moves.
Designs CDC and outbox patterns, schema boundaries and a safe order for moving data.
Builds policy gates, SBOMs, scans and approvals into pipelines, so security improves as you modernise.
Trust and control
Scans, SBOMs and approvals run in the pipeline before anything reaches production.
Routing, feature flags and canaries are designed with a way back before extraction starts.
Monitoring baselines and SLOs make every traffic shift measurable and reversible.
Approvals and release history are recorded for every modernisation release.
You keep full ownership of the code, configuration and documentation we create, with no vendor lock-in.
We pick what fits your product and team, not the other way round.
Results
We helped a logistics company split a growing all-in-one application into separate services for orders, dispatch, tracking, notifications and billing. Each area can now improve and scale on its own.
We redesigned a SaaS company's subscription and billing workflows as separate services for plans, payments, invoices, entitlements and notifications. Processes that affect revenue are now easier to manage and to recover when something fails.
We moved a global core banking system from an ageing mainframe to AWS one function at a time, keeping both ledgers in sync throughout. Operating costs fell 60%, releases became 5x faster, and there was zero service downtime.
We built AI network security for a global resort chain. It learns how devices normally behave on guest Wi-Fi and isolates suspicious ones automatically. It neutralised 99.9% of threats and detected them 2.5x faster.
It depends on the size of the monolith, how tangled the code and database are, and how many services you plan to extract. Because traffic moves gradually, the first services can go live while the rest of the system keeps running. A scoped project can kick off in 1–2 weeks, starting with a boundary review.
We use the strangler pattern: new services take over one route at a time while the monolith keeps serving everything else. Feature flags and canary releases send a small share of traffic first, and every step has a rollback path. Monitoring baselines show whether each shift is safe before more traffic moves.
We give each new service its own schema and move data in an order that follows the service boundaries. Change data capture (CDC) and the outbox pattern keep old and new data in step during the move, and anti-corruption layers stop the old data model leaking into the new services.
A distributed monolith is a set of services that still share database tables or must be deployed together, so you pay the costs of microservices without getting the benefits. We avoid it by agreeing boundaries and contracts first, and by making sure each service owns its own schema and can be released on its own.
The boundary review names the first services to extract and how to cut them over. A good first candidate changes often, causes release pain and has few links to the rest of the code. Our logistics and subscription billing clients split out areas such as orders, dispatch, tracking, invoices and payments.
You own 100% of the code, designs and IP, including the new services, pipeline definitions and infrastructure scripts. This is written into the service agreement. We can sign an NDA before you share your codebase, and the repeatable process we set up lets your own team extract further services later.
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