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Capability 04

Artificial Intelligence, Machine Learning & Automation

From a quantized model on a laptop GPU to a retrieval-augmented pipeline over proprietary data -- the full range of applied AI work.

All capabilities
CUDALangChainRAGPyTorch

What's inside

Local AI Development & Acceleration

Local environments tuned with NVIDIA CUDA and adjusted context windows to run quantized LLMs on high-end GPUs.

AI/ML Enterprise Solutions

Models trained, evaluated, and deployed -- from decision trees to deep neural networks -- to support faster, better-informed decisions.

AI Orchestration & RAG

Backend workflows using retrieval-augmented generation and agentic frameworks like LangChain to connect LLMs to proprietary databases and file systems.

What you get

  • A scoped model pipeline -- from a quantized local LLM to a hosted enterprise model
  • RAG connected to your own proprietary data, not a generic public knowledge base
  • Agentic workflows built on frameworks like LangChain for multi-step automation
  • An evaluation harness so you can measure whether the model is actually working

Configure AI workflow

Send this straight to the team, add it alongside other pillars in a single scope request, or pull a printable one-pager for internal sign-off.

Not sure this is the right pillar?

Browse the full capability set, or send us what you're building and we'll point you at the right one.

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