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//  Engineer custom software

AI-Native Development

// 01  What we deliver

What we deliver

LLM application architecture

Applications designed around streaming, retries, fallbacks and partial results, because non-deterministic output is a normal condition rather than an error case.

RAG pipelines and vector databases

Chunking, embedding and retrieval built and tuned against your corpus, with pgvector or a managed store, and retrieval quality measured rather than assumed.

Evaluation suites before release

Behaviour measured against a test set of real cases, so a prompt or model change is assessed on evidence.

Prompt management and versioning

Prompts held in version control with staged rollout, so a change can be traced and reverted like any other deployment.

Token cost and latency monitoring

Spend and response time budgeted per feature and monitored in production, because an assistant nobody waits for is not used.

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