Backend, cloud and AI work that holds up in production.

Six ways we help, from a first version to the platform you already run.

Backend

APIs & backend systems

The part of your product users never see and always feel. We design services, APIs and data models that stay simple as features pile up, so the next change doesn’t mean a rewrite.

What’s included

  • API design and implementation, with clear contracts and versioning
  • Data models on PostgreSQL, MySQL or Firestore
  • Background and scheduled jobs that run once, on time
  • Integrations with payment, messaging and partner APIs
  • Automated tests at every level: unit, integration and end-to-end

Typical stack

  • Java
  • Spring Boot
  • JPA
  • Node.js
  • NestJS
  • PostgreSQL
  • MySQL
  • Firestore
  • Elasticsearch

Related reading

How one hanging API takes down a whole Spring Boot app · Why your Spring Boot @Scheduled job runs twice (and what actually stops it)

Scale

Scaling & modernisation

When a system slows down at peak times, or every release feels risky, the answer is rarely a rewrite. We find the bottlenecks and fix them in place, one measurable step at a time.

What’s included

  • Performance audits of queries, data access and hot paths
  • Caching with Redis, and at the edge with Cloudflare
  • Moving in-memory caches and queues to Redis, RabbitMQ or Kafka, so services can scale out
  • Stateless, containerised services that run safely on many instances
  • Breaking up a monolith gradually, behind a gateway
  • Stabilising a system you’ve inherited

Typical stack

  • Redis
  • RabbitMQ
  • Kafka
  • Docker
  • Kubernetes
  • Cloudflare

Related reading

How one hanging API takes down a whole Spring Boot app · Why your Spring Boot @Scheduled job runs twice (and what actually stops it) · The case of the vanishing JobRunr runs

Cloud

Cloud infrastructure

Infrastructure that’s boring in the best way: reproducible, observable and sized for where you are now, not where you might be in five years.

What’s included

  • AWS setup: EC2, Lambda, databases and storage
  • Docker images and Kubernetes deployments
  • CDN, DNS and domains, including Cloudflare
  • A release process you can repeat, and production support
  • Monitoring and health checks that tell you before your users do

Typical stack

  • AWS EC2
  • AWS Lambda
  • Docker
  • Kubernetes
  • Cloudflare
  • Firebase

Product

MVPs & web apps

A first version that’s quick to ship and built so it doesn’t have to be thrown away, with features that feel instant.

What’s included

  • MVPs and web apps with React and Node.js
  • Real-time features on Firebase: live updates, bidding and notifications
  • Backends and APIs for mobile apps
  • Sign-in, roles and admin tools

Typical stack

  • React
  • Node.js
  • NestJS
  • MongoDB
  • Firebase
  • Firestore

Related reading

Going, going, gone: closing Firebase auctions on time

Automation

Automation & integrations

Work that should happen without anyone clicking a button: browser automation, scheduled processing, and systems that talk to each other reliably.

What’s included

  • Web and browser automation (RPA) with Selenium
  • Scheduled and background jobs with retries and alerts
  • Event-driven workflows on queues
  • Integrations between your systems and third-party APIs

Typical stack

  • Selenium
  • Spring Boot
  • Quartz
  • JobRunr
  • RabbitMQ
  • Kafka

Related reading

The case of the vanishing JobRunr runs

AI

AI integrations

AI features that are useful and safe to run: connected to your real data and systems, with clear limits on what they can see and do.

What’s included

  • LLM features inside your product: search, summaries, drafting and extraction
  • MCP servers that give AI assistants controlled access to your tools and data
  • Guardrails: permissions, logging and cost limits

Typical stack

  • MCP
  • LLM APIs
  • Java
  • Node.js

Not sure which of these you need?

Tell us what you’re building and where it hurts. We’ll reply by email to set up a short call.

Get in touch