LLM features, autonomous agents, RAG pipelines, and evaluation harnesses — engineered by a senior team that ships production AI, not demos. OpenAI, Anthropic, LangChain, and vector DBs, wired to your product with guardrails, cost control, and observability from day one.
Starts at $499 · Typical range $499–$2,499 · Model-agnostic
What you get
Every engagement pairs senior engineering, product design, and AI expertise on a single small team. No account managers, no sub-contracting — the people writing the code are on your calls.
How it works
Outcomes
Every feature ships against a measurable target — task completion, deflection, time saved. If it doesn't move the number, it doesn't ship.
Cost per request tracked from prompt one. We regularly cut inherited AI bills by 60–80% with the right model, cache, and prompt strategy.
Your evals, your retrieval index, your fine-tunes — durable artifacts that stay yours, not the model provider's.
Process
Where AI actually earns its keep in your product — and where it's a distraction that burns credits.
Ship the sharpest feature behind an eval harness. Measure real accuracy, not vibes.
Guardrails, caching, fallbacks, observability. Load-test the real user path.
Flag-gated rollout, telemetry, weekly eval iteration until the target metric moves.
The difference
Stack we ship on
Deliverables
You own the repo, the model configs, the evals, the dashboards. No lock-in, no repo held hostage, no black-box handoff.
They cut our LLM bill by 71% in the first month and shipped the eval harness we should have built a year ago.
FAQ
Model-agnostic. We choose GPT-5.x, Claude, Gemini, or open-source (Llama, Mistral, Qwen) per task based on quality, cost, latency, and privacy. Architecture supports hot-swap without a rewrite.
When the task is bounded, tools are well-defined, and there's a human-in-the-loop for the last mile — yes. When it isn't, we'll tell you 'workflow' beats 'agent' and save you months.
Retrieval grounding, structured output schemas, and evals proportional to risk. Financial, medical, and legal contexts get stricter treatment — including citations and refusal patterns.
Cost per request is instrumented from day one — model choice, semantic caching, prompt compression, and batching. Weekly cost review during the build.
When it earns its keep — typically for style, structured output, or domain vocabulary. Retrieval + strong prompting solves 80% of cases first.
30-min intro call. No slides. We diagnose the shortest path from where you are to shipped.
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