Your AI. Your servers. Your data.
AI & Automation Engineering
We deploy AI where it makes sense: on your infrastructure, under your control, solving real problems. Local LLMs, MCP integrations, and intelligent automation for infrastructure and development workflows -- not hype, not chatbots, not "AI-powered" marketing fluff.
Why This Matters
AI is genuinely useful -- but most of what's being sold to businesses right now is overpriced, overpromised, and sends your data to someone else's servers. There's a better approach.
Local AI deployment means:
Privacy
Your code, your documents, your business data never leave your servers. Critical for healthcare, finance, legal, and any company that values IP protection.
Cost control
After initial setup, there are no per-token fees, no monthly subscriptions, no usage-based billing that scales with your team.
Customization
Models can be fine-tuned on your codebase, your documentation, your domain vocabulary. Generic AI can't do this.
No vendor lock-in
You own the hardware, you own the models, you own the data. Switch tools anytime without losing anything.
Our Approach
We don't sell AI as a magic solution. We identify specific, measurable use cases where AI provides real value -- then we build and deploy the infrastructure to support them.
Identify use cases
Where in your workflow would AI actually save time or improve output? Code assistance? Documentation search? Data analysis? Automation?
Select models
Choose the right model for the job. Not every task needs GPT-4-class intelligence. Smaller, faster models often outperform on specific tasks.
Deploy infrastructure
Set up GPU servers, model serving, and integration points. Everything runs on your hardware or your cloud account.
Integrate workflows
Connect AI capabilities to your existing tools: IDE integration, Slack bots, CI/CD pipeline analysis, automated code review, documentation generation.
Train and hand off
Your team learns how to use, maintain, and extend the system. We document everything.
What You Get
When You Need This
“We want AI code assistance but can't send code to OpenAI”
We'll deploy a private code LLM on your infrastructure with IDE integration.
“Our internal documentation is a mess and nobody can find anything”
We'll build a RAG pipeline that lets your team ask questions in natural language and get answers from your docs.
“We want to automate infrastructure monitoring analysis”
We'll set up MCP integrations that let AI agents analyze logs, identify patterns, and suggest fixes.
“Our team wastes hours on repetitive tasks”
We'll identify the highest-value automation opportunities and build AI-powered workflows to handle them.
Technologies We Use
Featured Result
Client
Healthcare SaaS company (HIPAA-regulated)
Problem
Engineering team wanted AI coding assistance but couldn't use cloud-based tools due to HIPAA restrictions. Manual code review was slowing down the team by 10+ hours/week.
What We Did
Deployed Qwen 2.5 Coder on dedicated GPU hardware. Integrated Aider and Continue.dev into their VS Code workflow. Built a RAG pipeline over their internal documentation and codebase using ChromaDB.
Result
40% increase in developer velocity. Zero data leaves their infrastructure. $0/month in AI API costs after initial setup.
Ready to Deploy AI That You Own?
Book a free consultation. We'll help you identify the highest-value AI opportunities in your workflow.