We help you go from idea to running AI infrastructure on your own systems. Whether you're starting from scratch or adding AI to existing infrastructure, we handle the full journey: model selection, hardware planning, deployment, tooling, and training.
Most clients come to us with a use case, not a technical plan. That's fine. We figure it out together.
We begin with what you're trying to accomplish. Chatbot for internal teams? Document processing? Coding assistant? The use case drives everything else.
Before any hardware is purchased, we let you test drive models running in the cloud. You get to see how they perform on your actual tasks and confirm they meet your needs.
Once you've picked a model, we spec out hardware that matches your performance requirements, budget, and future scaling plans. Most clients start from scratch with a purpose-built GPU server.
Once your hardware is ready, we configure the AI stack: inference engine, model optimization, and integration with your existing data systems.
A running model isn't useful on its own. We set up the applications that let your team actually use it: chatbots, knowledge bases, coding tools, custom interfaces.
We document everything and train your team so they can manage the system themselves. You're not dependent on us to keep things running.
We don't just deploy a model. We build out the full stack that makes it useful for your team.
The core server that runs your model, tuned for your specific performance and concurrency requirements.
Internal chatbots with conversation history, user management, and access controls. A private alternative to ChatGPT that runs on your systems.
Connect your documents, policies, and institutional knowledge to the model. Includes document parsing, embedding, and retrieval so the AI can answer questions about your data.
Code completion and AI-assisted development tools integrated into your team's workflow.
For specialized data formats or unique workflows, we build custom parsing and processing pipelines tailored to how your organization works.
Real-time visibility into system health, performance metrics, and usage.
Load testing and benchmarks so you know exactly how your system performs under real conditions.
API guides, integration documentation, and hands-on training so your team can manage the system themselves.
Have a use case in mind? Let's talk through it and figure out the right approach.
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