Our group uses a niche EHR — can you still work with our data?

Yes. We work from structured data exports and de-identified text extracts rather than requiring live EHR access. The specific EHR platform doesn't determine feasibility.

We don't have an IT team. Who manages the deployed model?

We design deployments to run with minimal operational overhead. Lightweight inference infrastructure can run on hardware you already own, with update cycles managed by RonanLabs.

How much data does a specialty practice need to fine-tune a useful model?

Useful specialty adapters can be trained on modest data volumes — several thousand de-identified encounters is often sufficient for documentation tasks. We assess data volume and quality in the initial scoping phase.

Is the model specific to one physician or the whole group?

Typically the group, with optional per-provider style tuning. The group-level model carries the collective documentation conventions; provider-specific adapters can be added for physicians with distinctive patterns.

What happens if a provider leaves the practice?

The model is trained on group-level patterns, not personal data. Provider departures don't affect model ownership or performance.

Medical Groups & Specialty Clinics

AI that knows how your specialty actually works.

Ambulatory workflows, specialty-specific protocols, and practice-owned data — built for groups that move faster than hospitals.

Medical groups occupy a different position than hospitals: more agile, more specialty-focused, and often constrained by smaller IT teams and tighter margins. RonanLabs builds AI infrastructure calibrated for that operating reality — starting with narrow deployments that prove value before expanding.

The data problem in medical groups & specialty clinics

Specialty clinics generate dense, domain-specific data that generic AI tools are not trained to interpret. A plastic surgery practice, an orthopedic group, or a gastroenterology center each uses terminology, procedure codes, and documentation conventions that don't map cleanly to general clinical AI.

Most ambulatory AI tools are designed around primary care workflows and bolt on poorly to specialty settings. Specialty-specific nuance — procedure technique notes, device-specific outcomes, subspecialty coding — is treated as noise rather than signal.

Practice-owned data sits in EHR systems that were never designed for AI extraction. Moving that data to a cloud AI vendor raises HIPAA exposure questions most groups are not staffed to evaluate. The result is paralysis: everyone knows AI matters, but no clear path forward.

Smaller IT teams mean deployment friction matters more than in hospital systems. A solution that requires dedicated infrastructure staff to maintain is not viable for a 20-physician group without internal data science capability.

What we deliver

Synthetic data

Specialty-specific synthetic patient populations that mirror your practice's case mix — usable for staff training, EHR configuration testing, and model development without touching real patient records.

Custom models

Lightweight adapters trained on your de-identified practice data that layer on top of a general clinical foundation model, tuning the model's behavior to your specialty's documentation and decision patterns.

Knowledge & retrieval

A structured index of your protocols, procedure notes, and clinical references, queryable by the AI so it retrieves relevant context rather than relying on general medical knowledge alone.

See the full architecture for how these layers fit together.

Common deployments

Specialty documentation drafting

Pre-operative and post-operative note templates generated from procedure codes and dictation, formatted to the group's standard documentation patterns.

Clinical reference retrieval

Staff-facing tool that retrieves relevant protocol, device, and CPT guidance with citations, reducing lookup time during patient encounters.

Outcomes tracking and pattern detection

Models trained on the practice's longitudinal data to surface outcome trends across procedures, providers, and patient populations.

Training and onboarding support

Synthetic case scenarios used for new provider orientation, with the practice's own documentation patterns as the reference standard.

Frequently asked

Discuss your medical groups & specialty clinics deployment

Tell us about your data, your constraints, and your workflows. We'll design the layers around them.

Start the conversation