Healthcare & Life Sciences
Healthcare.AI that runs inside your own environment.
Fine-tune open models for clinical documentation, clinical reference lookup, patient communication and EHR data extraction, inside your own environment. Train and run on your own hardware and no PHI goes to a third-party API.
- Where it trainsSelf-hostWith Langtune, on your own hardware.
- BAAWe do not offer oneRun Langtrain inside your own HIPAA-covered environment instead.
- PHI sent to third-party APIsNoneWhen you train and run on your own hardware.
The problem
Major LLM providers now sign BAAs, so a hosted API is not automatically off-limits for US healthcare. In some cases a BAA is not enough and the data has to stay inside your environment, and clinical work still needs a model trained on domain-specific material.
- Image and vision inputs
- Data-residency rules outside the US, such as India's DPDP
- Objections to the sub-processor chain
- Government or classified work
How Langtrain helps
Purpose-built for Healthcare & Life Sciences.
Runs Inside Your Environment
We do not offer a BAA. Train with Langtune on hardware inside your own HIPAA-covered environment, so PHI is never processed on our infrastructure.
PHI Stays In Your Network
When you train and serve on your own hardware or private cloud, fine-tuning on clinical notes, EHR data and medical records stays inside it.
Medical Domain Fine-tuning
Train on clinical guidelines, coding manuals and your own clinical notes, then test it on cases you hold back.
Weights You Control
The trained model is a set of standard weights on your own storage. You decide who can run it, and your own logging covers every query.
Structured Extraction
Fine-tune on your own clinical notes to extract structured fields, and call the model through the API from your existing systems.
Runs At Each Site
Each hospital can host its own copy of the model, so patient data stays at the site that owns it.
Applications
What teams actually build.
- 01
Clinical Documentation
Structure physician notes into SOAP format and draft ICD-10 codes.
The treating clinician signs off.
- 02
Clinical Reference Lookup
Find the relevant guideline, drug interaction or protocol section for a question, with a pointer to the source.
A clinician makes the decision.
- 03
Patient Communication
Draft plain-language explanations of diagnoses, discharge instructions and medication regimens.
A clinician reviews before it is sent.
- 04
Prior Authorization
Draft prior authorization requests from the clinical justification in the notes.
Staff review before submission.
Check it first
Don't take our word for it. Test it on your own cases.
- 01
Hold back real cases
Keep 50 to 100 real examples out of the training data, with the answers you would accept.
- 02
Ask both models
Put the same questions to the base model and to your fine-tune, and read the answers side by side.
- 03
Have an expert review
Before anything ships, a clinician checks the answers and decides whether it is good enough.
How to run it: the quick start
No certifications yet: we have not completed a SOC 2 or ISO 27001 audit. For regulated data, train in your own environment.
Ready for Healthcare & Life Sciences?Start with your own data.
Talk to us, or start fine-tuning on the free plan.