GofarAI Labs · on-premise AI for US healthcare
Open-source AI. Running inside your hospital.
We tune small open-weight language models for healthcare workflows and ship them as complete on-premise deployments. Hardware, platform, models, and workflow tools — installed inside your building. Patient data never leaves.
Llama · Qwen · Gemma · Phi · Mistral · vLLM · LoRA · MCP
The Thesis
Hospitals shouldn’t send patient data to the cloud.
Modern language models transformed what software can do — but the biggest hospitals in the US still can’t safely use them. Sending PHI to a cloud vendor is a compliance nightmare. The big proprietary models are expensive, opaque, and slow to adapt.
GofarAI Labs takes open-weight models, tunes them for specific healthcare workflows, and ships them as complete on-premise deployments. Same capability. None of the exfiltration risk. Priced for a real hospital budget.
The Stack
The full stack, installed on your premises.
Five layers, one deployment. Every layer designed to keep patient data inside your building.
Layer 01
Hardware
We spec, source, and install the server and GPU on premise — or certify hardware you already own.
Layer 02
Platform
Inference server, model manager, audit logging, role-based access, encryption at rest. No external calls.
Layer 03
Models
Tuned open-weight models in the 7B–14B range. Swappable as better open models ship. Department isolation available.
Layer 04
Tools
Modular workflow plugins. Start with one, add more over time. Same server, same models, more value each quarter.
Layer 05
MCP Gateway
Every agent-to-agent interaction inside your hospital is inspectable. Policy enforced. Fully logged.
Tool Modules
Workflows your teams use every day.
Read → extract → classify → draft. Same engine, different prompts. A human approves every output.
PDF Batch Processing
Page-by-page OCR, structure extraction, and summarization across large document stacks.
Fax & Referral Triage
Classify inbound documents, extract key fields, route to the right department queue.
Prior Authorization Drafting
Assemble clinical justification letters from chart notes. Human clinician reviews and signs.
Denial Letter Analysis
Extract denial reason codes, suggest appeal grounds, draft appeals for the revenue cycle team.
Coding Assistance
Suggest ICD-10 and CPT codes from encounter notes for human coders to verify.
Discharge Summary Drafting
Assemble discharge summaries from chart data. Physician reviews and signs off before release.
Chart Summarization
Condense transferred records before appointments so clinicians walk in prepared.
Audit Preparation
Search and compile documentation for Joint Commission and payer audits in hours, not weeks.
Open Source Position
Open where it should be. Closed where it must be.
A clean legal and philosophical line, drawn in the same place every time.
We open-source
- Training recipes and tuning pipelines
- Evaluation benchmarks for healthcare tasks
- Synthetic and de-identified datasets
- Deployment tooling and platform code
- Base model weights tuned on public data
We never open-source
- Anything trained on real patient data
- Client-specific model adapters
- Client-specific evaluation results
- Anything that could reidentify individuals
- Weights that ever touched PHI
Security & Auditability
Every inference. Every interaction. Inspectable.
Nothing calls out. Every prompt, every completion, every tool invocation is logged inside your building. When other vendors’ AI agents show up in your hospital, the MCP gateway becomes the trusted control point: which agent can call which tool, with what data scope, all reviewable.
Small models tuned on real workflows outperform generic giants. We train LoRA and QLoRA adapters on your existing GPUs, overnight or on weekends. PHI never leaves the building. No data transfer agreements. No cloud round-trip.
Fine-Tuning as a Service
We tune. On your hardware. On your data.
Build the AI substrate for your hospital.
A short call. We map your workflows to a deployment plan, walk through the security model, and share references.