Live
Practice 01 of 04
AI & LLM Engineering
We design and ship applied-AI systems that hold up in production — from retrieval-augmented generation and agentic workflows to fine-tuned open models served behind real APIs.
- RAG & LLM Applications
- Agentic Workflows
- Model Fine-Tuning
- On-Device & Edge AI
What we deliver
Where we go deep.
Production LLM systems, RAG pipelines, agentic workflows, and model fine-tuning.
- 01
RAG & LLM Applications
Retrieval-augmented systems with hybrid search, reranking, and evaluation — grounded answers over your own data.
- 02
Agentic Workflows
Multi-step agents that plan, use tools, and act safely, with human-in-the-loop where it matters.
- 03
Model Fine-Tuning
Task-specialized open models (LoRA/QLoRA) with reproducible evaluation against real baselines.
- 04
On-Device & Edge AI
Quantization and ONNX conversion for privacy-preserving, offline-first inference on constrained devices.
Built by this practice
Running in production.
Retrieval, agents, and model infrastructure — applied AI that runs behind a real API and gets evaluated.
All ai & llm platforms
How we engage
A process built for clarity.
- 01
Discovery
We start with your problem and constraints — what success looks like, and what it will take to get there.
- 02
Plan & Estimate
A clear scope, milestones, and a realistic timeline, so you know what you're getting and when.
- 03
Build & Deploy
Iterative delivery with working software at each step — containerized and shipped, not left in a notebook.
- 04
Support & Iterate
Once it's live, we monitor, maintain, and improve it under real-world use.
Other practices
Let's talk
Have a problem worth solving?
Tell us what you're building. We'll help you scope it, build it, and ship it.