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Backend systems

The backend is invisible until the moment it is the only thing that matters.

APIs, data, and infrastructure built to stay fast, stay up, and not buckle when the traffic and the AI layer both show up at once.

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Practices

Four things we build on the backend.

APIs & Services

The contract your product, your app, and your partners all build against. Clean REST or GraphQL APIs in FastAPI, Django, or Node, versioned so a change does not break every client at once, and documented so nobody has to read the source to use them.

Data & Databases

Where your data lives and how fast you can ask it questions. Schema that survives growth, Postgres tuned for real queries, vector databases for AI retrieval, and migrations that do not need a maintenance window. The one layer you cannot casually rewrite later.

AI Backends

The infrastructure your AI features actually run on. Model gateways, embeddings and vector stores, retrieval, request queues, caching, and the cost and rate controls that stop one runaway loop from torching your budget. The plumbing between your product and the model.

Jobs & Pipelines

The work that should never happen inside a web request. Background jobs, queues, scheduled tasks, retries, and data pipelines, so a slow export, a batch of embeddings, or a long inference run happens out of band and never freezes the user. Reliable, retryable, and observable.

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