About GofarAI Labs
Building the AI substrate for US healthcare.
Open-source, on-premise AI shaped for how hospitals actually work — not adapted from consumer tooling, not bolted onto an EHR, and not sending your patients’ data to someone else’s cloud.
The Thesis
Hospitals cannot safely send PHI to a cloud LLM.
The AI revolution has left US healthcare stuck. Frontier cloud models are powerful but incompatible with HIPAA-grade data control. Big vendors are slow, expensive, and treat hospitals as feature backlog items.
Open-weight small models — Llama, Qwen, Gemma, Phi, Mistral — are now good enough that a well-tuned 7B or 14B model, running on hospital hardware, beats a generic frontier model on real hospital tasks. We take that starting point, tune it for specific workflows, and ship it as a complete on-premise deployment.
The result is a stack hospitals can actually use: HIPAA-friendly by architecture, tuned for real jobs, priced for a real hospital budget.
How We Work
Three ways we’re paid. One thing we sell.
A working AI substrate inside your hospital. The commercial structure is straightforward.
01
Install
One-time hardware and platform setup. We spec, source, install, and configure the stack. Your infrastructure. Your control.
02
Subscription
Platform license, model updates as better open weights ship, new tool modules, and support. Recurring. Predictable.
03
Tuning Engagements
Consulting engagements where we tune models on your hardware and your data. Deep, high-margin, and how we get better at the whole business.
What We Believe
Principles.
- Patient data stays inside the hospital. Full stop.
- Open-source is a moat, not a marketing checkbox. Recipes and evaluations are public so hospitals can verify what they’re getting.
- Small tuned models on the right hardware beat generic giants on real work.
- Every output has a human reviewer. The model drafts. Your team decides.
- Speed is not the selling point. Privacy, control, and auditability are.
- Hospitals don’t buy models — they buy working solutions. So we ship the full solution.
Founder
Jamal Hajizada — Founder & CEO
Jamal is an AI engineer and systems architect with over a decade of experience designing, building, and deploying production software and data systems, specializing in local LLM deployment and fine-tuning. His focus is deploying and fine-tuning local, open-weight language models inside privacy-sensitive healthcare environments — the same architecture GofarAI brings to hospitals. He works hands-on across the full stack: local LLM deployment, retrieval-augmented generation (RAG), LoRA/QLoRA fine-tuning, and Linux infrastructure. He holds an M.S. in Information Systems from California State University, Los Angeles. Jamal leads GofarAI’s technical direction and every engagement; specialized engineering hires are planned as pilots convert.