The Platform
The full stack, installed on your premises.
Five layers. One deployment. Every layer designed to keep patient data inside your building. Hospitals don’t buy models — they buy working solutions. We ship the full solution.
Layer 01
Hardware
We specify, source, and install the server and GPU on premise — or certify hardware you already own. A single 24GB card runs a quantized 8–14B model well for document workflows. Larger clients get multi-GPU boxes with department isolation between models.
Speed is not the selling point. Privacy and local control are. Hospitals accept slightly slower processing in exchange for data never leaving the premises.
Layer 02
Platform
The installable GofarAI package sits on top of your hardware. This is where HIPAA-friendly architecture lives.
- Inference server (vLLM or llama.cpp)
- Model manager — swap models as better open weights ship
- Audit logging of every inference, prompt, and completion
- Role-based access controls
- Encryption at rest
- Zero external calls — the platform never phones home
Layer 03
Models
Tuned open-weight small models in the 7B–14B range. Swappable as better open weights ship — you’re never locked to a single vendor’s roadmap.
Multi-model deployments for larger hospitals
- Specialization by role — one model for revenue-cycle language, another for clinical documentation
- Department isolation — separate fine-tunes so weights never mix information domains (important for 42 CFR Part 2 behavioral-health data)
- A small router-classifier model in front decides which LLM handles each request
Layer 04
Tools
Workflow tools are modular plugins on the platform. You start with one, add modules over time. Same server, same models, more value every quarter.
Every tool follows the same shape: read → extract → classify → draft, with a human approving. Same engine, different prompts and output templates.
Layer 05
MCP Gateway
The GofarAI box exposes its tools as MCP endpoints, so authorized agents — EHR-adjacent systems, other vendors’ agents, future AI purchases — can call them via a standard protocol. It also acts as an MCP client, letting the local LLM call other hospital systems (scheduling, labs, bed management) that expose MCP endpoints.
The gateway enforces policy: which agent can call which tool, with what data scope, all logged. As hospitals accumulate more vendors’ AI agents, this becomes the trusted control point — every agent-to-agent interaction is inspectable.
See the stack in your environment.
A short call. We map your workflows, walk through the deployment plan, and answer your security team’s questions.