On-Premise AI Strategy & Advisory

No. We are independent consultants, not hardware vendors. We design the blueprints, spec the exact procurement bills of materials, and provide implementation oversight. You purchase the hardware directly, ensuring complete control over assets and zero vendor lock-in.

Physical appliances (such as dedicated GPU cluster servers) are ideal for regulated mid-market firms with strict physical facility audits and zero-egress mandates. For smaller teams or non-regulated businesses, we recommend deploying open-weight models inside a Private VPC (AWS/Azure) or using high-spec local workstations (Mac Studio), which provide data sovereignty at a fraction of the hardware maintenance overhead.

If you choose the on-premise hardware setup, 100% of data processing, vectorization, and inference occurs inside the physical box on your local network, and external internet access can be completely severed. If you choose a Private VPC, data remains encrypted within your private cloud instance and is never sent to public APIs or used for model training.

We typically benchmark and recommend quantized versions of leading open-weight models. As an illustration at the time of writing, models such as Llama 4 Scout (reported ~109B parameters with a long context window) suit long-context documentation processing, DeepSeek V4 variants are strong at logical reasoning and coding (licensing varies by release — we verify the current licence at selection time), and Qwen 3.6 or Mistral Large 3 do well in multilingual and agentic workflows. Model names and specs move quickly; selection is highly dependent on your specific use case, so we evaluate, run local tests, and recommend whatever fits best at the time of your engagement.

Yes. While we specialize in zero-egress open-weight model deployment, we build flexibility into your architecture. We can run local tests, prompt engineer, harness engineer, and deliver everything you need to leverage either local on-premise AI or your own chosen AI cloud provider. This includes native integration specs for AWS Bedrock, Azure AI, GCP Vertex AI, Anthropic, OpenAI, OpenRouter, Mistral, and DeepSeek, enabling you to switch providers with zero configuration rewrite.