Corti

The models are the company. Corti is a research and development organisation building healthcare foundation models and selling them as infrastructure through SDKs and APIs, including three healthcare specialised foundation models it states were trained exclusively on medical data and a clinical grade Danish speech to text model. Every product it ships is downstream of model work rather than a workflow wrapper with a model inside it.

The finest grained oversight model in this category, and structurally distinct from the other two strong approaches here. Rather than asking a clinician to proofread a finished narrative, FactsR surfaces atomic clinical facts as the consultation unfolds and lets the clinician review, accept or adjust each one live, after each fact has already passed an automated validation loop. Verifying a discrete extracted fact against what was just said is a materially easier and more reliable cognitive task than auditing a paragraph after the visit, which is where automation bias does its damage. This index now holds three distinct oversight architectures worth comparing directly: Abridge makes verification auditable through Linked Evidence, Speke makes it a human scribe's job, and Corti makes it atomic and concurrent.

The strongest transparency posture located in this category, on three separate grounds. Architecture is described mechanically rather than adjectivally: FactsR is set out as a four stage recursive loop with named behaviour at each stage, not as advanced reasoning. Models are shipped through documented API endpoints with distinct paths for structured transcription and real time streaming, so behaviour is inspectable by the developers integrating it. Most importantly, Corti built its Danish clinical speech model in partnership with the Alexandra Institute through the CoRal initiative, contributing to OPEN BENCHMARKS and shared Danish speech data so performance is measured against public standards rather than internal ones. That is the direct inverse of the unfalsifiable vendor generated benchmarking this index flags elsewhere. One caveat holding the grade honest: the headline claim of a 65 percent reduction in note bloat is vendor generated with no published methodology or comparison set.

Graded on what was retrieved for the ambient documentation product specifically, and that is thin. The 65 percent note bloat figure is vendor generated with no methodology. The frequently cited statistics about clinician AI attitudes come from surveys Corti commissioned with YouGov, which is market research rather than clinical evidence and is self interested by construction. The Alexandra Institute collaboration is real independent work but evaluates speech model accuracy, not clinical or operational outcomes. This is likely the most understated axis in the record: Corti has a research heritage in emergency call triage with a peer reviewed literature behind it, none of which was retrieved in this pass. Priority refresh candidate.

Strong on data control, unevidenced on data lifecycle. The sovereign cloud and on premise options mean a health system can keep clinical audio inside its own infrastructure and jurisdiction, which is the most substantive PHI protection available in this category because it removes the question rather than answering it. What was not located is the rest: retention periods for audio and transcripts, de identification practice, and an explicit statement on whether customer data is used to train Corti's foundation models, which matters more for a company whose business is model development than for an application vendor.

Not assessed, and the frame differs from the United States vendors here. Corti is European first and its stated compliance argument is built around the EU AI Act and data sovereignty rather than HIPAA. A United States buyer should establish the business associate agreement position separately rather than assuming it from the European posture.

Not assessed. No named or dated attestation was located in this pass.

No clearance claimed and none required for ambient documentation. Worth recording that Corti's regulatory positioning runs the other way from most vendors here: rather than treating regulation as a hurdle, it argues that running clinical AI inside United States anchored hyperscalers is itself a liability under the EU AI Act, and sells compliance and portability as the wedge. That is a commercial argument rather than a regulatory status, and it should be read as one.

Addresses the category's central failure mode by engineering rather than by disclaimer, which is unusual enough to credit even though it is not a governance disclosure in the conventional sense. Where other vendors either ignore accent and dialect degradation or name it in a limitations document, Corti builds language specific clinical models and states that its Danish model handles background noise, overlapping dialogue, regional accents, compound terminology and mixed language usage, developed with an independent research institute explicitly so that measured performance reflects real clinical language rather than clean test audio. Held at B rather than A because no fairness statement, subgroup analysis or published performance breakdown across speaker populations was located, so the work is asserted rather than shown.

Read this grade as a scoping fact rather than a deficiency. Corti deliberately sits one layer below the EHR question: it ships models and reasoning through SDKs and APIs and the integration into a record system is performed by the vendor or health system building on it, with partners such as Voicepoint in Switzerland delivering the finished documentation product. A health system evaluating Corti against a turnkey scribe is not comparing like with like, because the integration work that Abridge or Suki performs is here the buyer's or integrator's responsibility. No named EHR integrations were verified in this pass.

The clearest A on this axis anywhere in the ambient category, where almost every competitor is Not Rated. In July 2025 Corti launched what it describes as Europe's first sovereign healthcare AI cloud, designed to run on any cloud or on premise and to remain portable off any single vendor, with the explicit purpose of letting clinical AI run without residing in a United States anchored hyperscaler. This is the ambient documentation instance of the question this index tracks across categories, which is where the sensitive asset physically goes. Cardiac imaging splits on where the scan goes and drug discovery on where the chemistry goes; here the asset is recorded patient conversation, and Corti is the only vendor assessed so far that lets the buyer decide.

No published rate card. Sold as infrastructure through SDK and API relationships and through partners rather than as a per provider subscription, so no comparable per clinician figure exists.

Broad by setting rather than enumerated by specialty. Documented across emergency dispatch, primary care and telehealth, a spread that reflects the company's origin in emergency call triage and is unusual in a category dominated by outpatient office visits. Language coverage is deliberately deep rather than wide, with dedicated clinical grade models per language beginning with Danish, which is the opposite of the many languages one model approach competitors advertise. No specialty count published.