ClinicFrame vs Switchyard: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of ClinicFrame and Switchyard — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
ClinicFrame
ClinicFrame
Ambient AI medical scribe that transcribes visits in real time and delivers a structured SOAP note within seconds.
Key features
- Ambient Voice Capture: Runs on the clinician's laptop and records the patient visit in real time without requiring extra hardware, in person or on telehealth.
- Specialty-Trained Transcription: Reaches 96% transcription accuracy across 15+ medical specialties using models trained on specialty-specific clinical language.
- Structured Note Generation: Produces SOAP notes for medicine and DAP/BIRP notes for behavioral health seconds after the visit ends, plus configurable custom templates.
- EHR Copy-In: Notes can be pasted into Epic, Athenahealth, Cerner and Healthie in under 30 seconds, so it slots into existing charting workflows.
- HIPAA-Aware Handling: Audio is discarded after the note is generated and a signed Business Associate Agreement is available on request.
- Flat Monthly Pricing: Priced per clinician per month with no per-hour surcharges, replacing traditional human scribing services.
Best for
- Primary Care Documentation: A family physician sees back-to-back patients and finishes the day with SOAP notes already drafted, cutting after-hours charting time.
- Behavioral Health Notes: A therapist runs 50-minute sessions and gets DAP or BIRP notes generated automatically instead of writing them up between clients.
- Telehealth Visits: A remote clinician on a video call has the conversation transcribed and structured without a separate device or human scribe on the line.
- Multi-Specialty Clinics: A clinic covering cardiology, dermatology and psychiatry gets specialty-appropriate note formatting from a single tool.
- Scribe Cost Reduction: A practice that has been paying hourly for human scribes switches to a flat monthly software subscription.
Switchyard
NVIDIA
An open-source Rust proxy and library that routes LLM traffic across models and providers while preserving native OpenAI and Anthropic API compatibility.
Key features
- Protocol Translation: Converts between OpenAI Chat Completions, OpenAI Responses and Anthropic Messages formats so clients keep their native API while any backend serves the request.
- Multi-Backend Routing: Spreads traffic across vLLM, NVIDIA NIM, Ollama and any OpenAI-compatible endpoint, letting you point an existing coding agent at an open-source model without changing the agent.
- LLM Classifier Router: Uses request content to decide whether a given turn needs the weak or the strong model tier, cutting spend on turns that do not need frontier capability.
- Stage Router: Routes most turns from signals already in the conversation — tool results, errors, conversation stage — so no extra model call is needed to make the decision.
- Escalation Router: Runs every turn on the weak tier first, then has a judge read that answer and decide whether the same request should be re-sent to the strong tier.
- Random Routing for A/B Tests: Applies a fixed traffic split across targets for benchmarking, baselines and cost experiments.
- Operational Metrics: Exposes Prometheus metrics for requests, errors, latency, token counts and the overhead added by routing itself.
- Server or Library Deployment: Run it as a standalone Rust proxy configured by routes.toml, or embed switchyard-libsy in your own application so it decides the target and hands the model call back to you.
Best for
- Pointing Coding Agents at Open Models: Serve Claude Code or Codex from vLLM, NIM or Ollama without the agent knowing the API changed.
- Cost/Performance Optimization: Send routine turns to a cheap weak-tier model and reserve the strong tier for turns a classifier or judge says need it.
- Model A/B Benchmarking: Split traffic on a fixed ratio across two models to compare quality, latency and cost on real production requests.
- Provider Migration and Failover: Keep application code on one API shape while swapping or mixing the providers behind it.
- Embedding Routing in an Agent Runtime: Drop the routing algorithms into an existing gateway or agent framework via the library path without adopting a new HTTP stack.
- Operational Visibility: Track per-route latency, error rates and token spend through Prometheus to find which routes are actually costing money.