Engineering services

Organised around the problem rather than the technology: where data is created, how it moves, and how you know it arrived correctly.

Backend & distributed systems

We design and build backend services where concurrency, retries and failure are normal operating conditions rather than edge cases.

Go services, PostgreSQL, Redis
REST and gRPC APIs, WebSockets
Queues, workers and asynchronous processing
Idempotency, retries and concurrency control
Schema design that holds rules in the database, not only in code

System & API integration

We connect SaaS platforms, internal applications, third-party APIs, databases, financial systems and cloud services — and make the connection observable.

Data synchronisation and transformation
Validation at every boundary
Retries that are safe to repeat
Reconciliation between source and destination
Logs, traces and alerts that say which record failed and why

Data engineering & integrity

Some data passes through several systems before it matters: operational events become usage, usage becomes an invoice, an invoice becomes a finance record. We build the pipeline and the checks that prove it is right.

Operational events → transformation → downstream systems
Usage → billing → invoice → finance
Source system → integration → destination system
Traceability from any output back to its inputs
Exception datasets instead of silent drops

Applied AI

We integrate language models into existing applications as components with inputs, outputs and failure modes — not as demos.

LLM APIs and structured extraction
Retrieval-augmented generation, embeddings, pgvector
Hybrid search: full-text and semantic together
Document understanding for PDFs and images
AI-assisted workflows with human review

Cloud & production systems

We set up and run the environments these systems live in, from containers and workers to deployment pipelines and monitoring.

GCP: Cloud Run, Cloud SQL, Pub/Sub
Docker and Kubernetes
Background workers and scheduled jobs
Deployment environments and migrations that run safely
Monitoring, tracing and production reliability

Ways to work with us

Start small and bounded; grow when the first result is in your hands.

Focused engineering sprint
About 1–2 weeks
The easiest place to start: one clearly bounded technical problem, a fixed scope, and working output at the end — code, tests and findings you keep.
Engineering project
Several weeks to several months
A larger backend, integration, data, AI or infrastructure build, planned in milestones and delivered into your repositories.
Embedded engineering
A defined period
Senior backend engineering working inside your existing engineering or product team, on your tools and your process.

Technology

Backend: Go, PostgreSQL, Redis, REST, gRPC, WebSockets
Infrastructure: Docker, Kubernetes, GCP, Cloud Run, Cloud SQL, Pub/Sub
AI & data: OpenAI APIs, LLMs, RAG, pgvector, Embeddings, Hybrid search, Document processing
Frontend: React, Next.js

Have a system that has to be right?

Tell us where the data moves and where it goes wrong. The first conversation is technical: the systems involved, the boundary that matters, and what a first sprint would produce.

Discuss an engineering problem