API services
Public and internal APIs with authentication, pagination, versioning and rate limiting designed before implementation.
The language most of our backend work is written in.
Services, workers, integrations and data pipelines — written with types at the boundaries and tests around behaviour.
In this stack
The stack
Written as a reason rather than a feature list, because the reason is what tells you whether it applies to your project.
Modern typing features used throughout, so editors and CI catch mistakes before review does.
Our default for API services: typed routing, async I/O and OpenAPI docs generated from the code.
Chosen when the admin, ORM and conventions genuinely save months on a content- or CRUD-heavy product.
Validation and settings. Request, response and config shapes are declared once and reused.
Fixtures, factories and parametrised cases, wired into CI so coverage is enforced rather than reported.
Used where explicit query control matters more than ORM convenience.
Durable background work and scheduling, built to be idempotent and replayable.
Identical environments locally, in CI and in production — the cheapest class of bug to eliminate.
Applied
The kinds of systems this area of the stack is actually used to build.
Public and internal APIs with authentication, pagination, versioning and rate limiting designed before implementation.
Typed clients around third-party APIs with retries, timeouts and explicit error handling, so drift surfaces as a test failure.
Queues and scheduled jobs for imports, exports, notifications and anything that must survive a restart.
The service layer behind agents and retrieval systems: orchestration, validation, logging and cost control.
Where it is applied
FastAPI services, data-validation layers and automated test suites — Python backends built to be read, extended and trusted by whoever maintains them next.
02Support agents, document processing, lead qualification and multi-step workflows — built on retrieval over your own content, with evaluation and escalation designed in.
03Custom Model Context Protocol servers that expose your data and actions as typed tools — with authentication, scoped permissions and audit logging built in from the start.
Also in our stack
Three tools that make a Python API predictable.
Server-rendered by default, interactive where it matters.
Model calls are the easy part. The engineering is around them.
The connective tissue between the tools you already pay for.
Tell us what you are building and where it is getting difficult. You will get a straight technical answer before any commercial conversation.