LLM apps that ship and stay shipped.
Structured outputs, real evals, and cost discipline built in.
We build domain-specific LLM apps that hold up in production — not demoware that breaks in week two. Structured outputs you can rely on, evals that catch regressions, prompt caching that controls cost, and observability so you actually know what's happening at runtime.
Engineering, not slides.
Structured Outputs
Schema-validated JSON, tool-calling, constrained decoding. Your downstream code can rely on the shape.
Evals Pipeline
Regression tests for prompts. CI gates that fail on accuracy drops. No more 'it worked yesterday'.
Prompt Caching
Aggressive cache strategies on Anthropic / OpenAI / Bedrock. Often 60-80% cost reduction on read-heavy workflows.
Multi-Model Routing
Cheap model for easy tasks, big model for hard ones. Automatic fallback on rate limits or outages.
Document Processing
OCR + extraction + classification pipelines on PDFs, scans, photos. Built-in field-level confidence scoring.
Observability
Per-call tracing, token spend dashboards, latency p95s, output-quality scoring. You see what the model sees.
From idea to production.
Use-case framing
We translate 'use AI for X' into testable evaluation criteria before writing a line of code.
Baseline + evals
Build the eval suite first. Then build the system. Then measure both together.
Iterative shipping
Ship weekly, measure against evals, refine prompts/models/retrieval. No big-bang launches.
Handoff
Documentation, runbooks, dashboards. Your team can operate it without us.
Models & tools we reach for.
Common questions.
Why not just use ChatGPT?
For one-off tasks, do. For features inside your product, you need structure, evals, and cost control — that's where we come in.
What's a realistic timeline for a custom LLM feature?
First production deploy in 4-8 weeks for most use cases. Faster if requirements are sharp.
Do you do fine-tuning?
Yes — but we recommend it only when prompt engineering + retrieval can't hit your accuracy targets. Fine-tuning is the last lever, not the first.
Let's scope it together.
Free 30-minute call. Bring your problem statement and current stack — we'll tell you honestly whether it's worth the build.