Enablement that compounds
Deploying AI without training is buying a gym membership for someone else. We upskill your whole company — from the C-suite to the engineers — on the exact models and toolchain that fit your ecosystem, until your team runs it without us.
Half-day session: what edge AI realistically does, what it costs, what it protects. Walk out able to make confident investment decisions and kill the FUD.
Practical workshops: prompt craft, RAG over company knowledge, safe workflows, and how to spot when AI output needs a human. Built around your daily tools.
Hands-on: model deployment with Ollama/vLLM/llama.cpp, RAG pipelines, fine-tuning on your corpus, GPU sizing, monitoring, and secure operations.
Windows shop? Linux data center? NVIDIA everywhere or AMD on a budget? Apple fleet? There's a capable open model and runtime for every ecosystem — and we train your team on the one that fits yours.
We benchmark candidates against your actual workloads (documents, code, tickets, images) and teach your team not just how to run the chosen model, but why it won — so you can re-evaluate confidently when the landscape shifts.
We don't want to be your permanent crutch. We identify and intensively train internal champions — the people who keep the AI momentum alive long after the engagement ends.
Demystify LLMs, embeddings, RAG and fine-tuning. Plain-language mental models for non-engineers, honest limits included.
Why local inference, how your deployment works, data hygiene, and the policies that keep the whole company out of shadow AI.
Teams build their own RAG assistants, automations and copilots against their real documents — guided, on your private stack.
Engineers go deep: deployment pipelines, model evaluation, fine-tuning on internal corpora, monitoring and incident response.
Champions run a live project end-to-end with us observing. Documentation finalized, and we step back to advisory-only.
Tell us your team size and ecosystem — we'll scope a training program that fits, in a language your people actually speak.