Services that stay correct under load.
Anyone can build an API that works in the demo. We build the ones that hold their numbers on the worst day of the year — settlement runs, Black Friday, market open.
We design and build the services that carry core business logic: payment flows, order pipelines, ledgers, booking engines. The discipline is always correctness first — idempotency, transactional boundaries, well-defined failure modes — then throughput. Most of our work is in Go, Java, and Kotlin against PostgreSQL, because boring technology is what survives.
- 01 High-throughput service design and build
- 02 API design — REST, gRPC, and contracts
- 03 Monolith decomposition, done conservatively
- 04 Transactional and ledger systems
- 05 PostgreSQL schema design and performance
- 06 Load testing and capacity modelling
- 07 Legacy service rewrites with parallel-run cutover
- 08 Architecture review and failure-mode analysis
Discover
We read the code, trace the hot paths, and load-test the current system so the baseline is measured, not estimated.
Build
New services run in parallel with the old — same traffic, compared outputs — before any cutover. No leap-of-faith releases.
Run
Every service ships with dashboards, alerts, runbooks, and a tested rollback. Your on-call inherits a known quantity.
Do you rewrite, or work with what we have?
We default to working with what you have. Rewrites are a last resort with a high failure rate; when one is genuinely justified we de-risk it with parallel running and incremental cutover, never a big bang.
What does a typical team look like?
Two to four senior engineers, one of whom leads the engagement and is your single point of accountability. We deliberately stay small — small senior teams outship large mixed ones.
Why Go, Java, and Kotlin?
Because they are boring in the best sense: mature runtimes, predictable performance, deep hiring pools. We will work in your existing stack; we recommend these when the choice is open.
Who owns the IP?
You do. All code, schemas, and documentation are assigned to you. We bring patterns and experience, not a proprietary framework you get locked into.
How do you prove the new system is correct?
Shadow traffic and output comparison. The new service processes the same inputs as the old one for weeks before cutover, and every divergence is investigated. Correctness is demonstrated, not asserted.