AI features that survive contact with real users and real data.
We build AI agents, LLM apps, and custom ML models that run in production — not slide decks. Every feature gets an evaluation set before it ships, a cost ceiling before it scales, and a fallback for when the model is wrong.
What you get
- ModelsOpenAI, Claude, open-weight, self-hosted
- EvaluationTest sets before every release
- GroundingRAG with citations over your data
- PrivacyZero-retention or self-hosted options
- CostToken budgets and caching built in
Sound familiar?
The demo wowed the room, then the model started making things up in front of customers
You shipped a chatbot but can't measure whether it helps
Your OpenAI bill doubled last month and you're not sure which feature caused it
Legal won't sign off on sending customer data to a third-party model
You have years of data sitting in a warehouse and no predictions coming out of it
Vendors promise magic, but you need one workflow automated reliably
What we build
- 01
AI agents & automation
Agents that plan and execute multi-step tasks inside your tools — CRM, helpdesk, back office — with guardrails, approval steps, and a log of every action they take.
- 02
LLM apps & RAG
Chat and search over your own documents and databases, with retrieval that cites its sources so answers can be checked instead of trusted.
- 03
Custom ML models
Classification, forecasting, and computer vision trained on your data — for when a general-purpose model is too slow, too expensive, or simply not accurate enough.
- 04
Data pipelines & integrations
Pipelines that ingest and clean your data, plus evals, drift monitoring, and per-request cost tracking — so you catch degradation and bill spikes before customers do.
How it works
- 01
Discovery call
Tell us the workflow you want automated or the question you want answered, and what data you have. No commitment.
- 02
Scope & proposal
A fixed-scope plan with model choice, success metrics, and a running-cost estimate — before any code is written.
- 03
Build in sprints
An evaluation set first, then the feature, measured against it every sprint on a staging environment you can try yourself.
- 04
Launch & support
Deployment, monitoring, cost alerts, and a support window — plus retraining or prompt updates when the world changes.
Technologies we use
- OpenAI
- Claude
- DeepSeek
- Kimi
- PyTorch
- TensorFlow
- Hugging Face
- LangChain
- Scikit-learn
- OpenCV
- Python