Backend & API Development
Reliable services and APIs your product can be built on.
Almost every product problem that surfaces late - flaky features, security scares, data you can't fully trust - traces back to the foundation. A backend is invisible when it's right and everywhere when it's wrong. We design clear data models and documented APIs, build security and observability in from day one, and choose infrastructure that scales with you instead of against your budget.
A shaky backend shows up everywhere.
Flaky features, security gaps, and data you can't fully trust all trace back to the foundation. Fixing it after launch costs far more than getting it right early.
How we deliver.
Model the domain
Clear data models and contracts so every client can rely on consistent behaviour.
Secure by default
Authentication, authorization, and validation designed in - not patched on.
Observe everything
Structured logging, metrics, and alerts so issues surface before users feel them.
Scale deliberately
Infrastructure chosen to grow with load without ballooning your bill.
Everything to launch and grow.
Products we've shipped.
Read before you build.
Multi-tenancy: how to choose before it's expensive to change
Shared schema, database-per-tenant, or sharded? The deciding factor isn't cost - it's what happens when one customer needs something the others don't.
EngineeringMCP is stateless now: what the 2026-07-28 spec changes
The new MCP spec deletes the initialize handshake, sessions, and resumable streams. Your server becomes an ordinary HTTP service - and scales like one.
AIBackground agents: AI that finishes the job after you close the tab
Agents now run for hours at coin-flip reliability. That's why AI is moving from the chat box to durable background workflows that survive crashes and retries.
EngineeringJust use Postgres: one database instead of five
Postgres plus a few extensions now covers search, vectors, queues, documents, and jobs. Add a specialized system only when a real bottleneck forces it.
EngineeringDesigning a backend an AI agent can actually use
Agents retry, chain, and act unsupervised - so APIs built for humans break. Idempotency, structured errors, and observability make a backend agent-ready.
EngineeringYou probably don't need a vector database
The AI wave pushed everyone toward a dedicated vector database. For most apps, Postgres with pgvector does the job - one fewer system to run, secure, and sync.
EngineeringYour API needs an MCP server (and it's a security boundary)
AI agents are a new class of API consumer, and MCP is how they call your backend. The interesting work isn't the tools - it's auth, scoping, and audit.
EngineeringHow to design an API that lasts (2026)
How to design an API that survives real use: REST vs GraphQL, versioning from day one, and the backward-compatibility rules that stop you breaking clients.
EngineeringNode.js vs NestJS in 2026: choosing your backend stack
Node.js vs NestJS in 2026: NestJS runs on Node, it's not an alternative. When raw Express is right, when NestJS earns its structure, and where Fastify fits.
EngineeringSQL vs NoSQL in 2026: how to choose (start with Postgres)
SQL vs NoSQL in 2026: why Postgres is the safe default, when a document database actually wins, and how to choose without regretting it later.
Questions, answered.
Can you integrate with our existing systems?
Yes - we design APIs and integrations around the systems and data you already run.
Do you document the API?
Always. Clear, versioned documentation is part of the deliverable so your team and partners can build against it confidently.
How do you handle security?
Defense in depth: validated inputs, least-privilege access, encrypted secrets, and security reviewed at every layer.
Have a project in mind?
Tell us what you're building. We'll come back with a senior read on how to ship it.