aiomics
aiomics, a Berlin company founded by physician Sven Jungmann, sells a work platform for German rehabilitation and acute care clinics: a shared case workspace for physicians, nursing and therapy, with generative AI that prepares admissions, drafts physician and rehabilitation discharge letters with source comparison and omission checks, handles patient questionnaires, drafts responses in insurer case reviews (Falldialoge and Vorverfahren) and prepares billing evidence for private physician billing. Discrepancies between sources are flagged, and professionals review and release everything before use.
Patient data is processed only in the EU, is not used for model training and is isolated per clinic; aiomics is certified to ISO/IEC 27001:2022 by TÜV NORD CERT, with an application level C5 attestation in preparation. Named partners and customers include MEDICLIN clinics in Soltau, Breisach and Donaueschingen and the Charité, where an independent evaluation is underway. Raised a 2 million euro pre seed round in September 2025.
Capability Axes
An AI Health Index grade measures what a buyer can verify from public sources on the date shown. It is not a rating of how good the product is. A vendor can build an excellent system and grade low on an axis because it publishes nothing an outsider can check. How grades read
The models are the engine of the core modules, and the platform carries other value. aiomics now presents itself as a work platform for clinics: a shared case workspace with Kanban views, task ownership and handovers between physicians, nursing and therapy, plus patient questionnaires (PROMs and PREMs).
Its generative AI drafts physician and rehabilitation discharge letters with source comparison and omission checks, prepares admission documents, drafts responses in case reviews with insurers and prepares billing evidence. The workspace and questionnaires carry value without the models.
What the system may and may not do are published, with the review path. aiomics prepares, compares and drafts; before anything is used further, professionals review and release it ('Vor Weiterverwendung: fachliche Prüfung und Freigabe'). Where two sources disagree, the case view flags the discrepancy and the team resolves it against the original, and drafts carry source references and omission checks. Access and workflow scope are agreed per deployment. The residual risk is a reviewer releasing drafts at speed, and nothing published shows how often released letters are edited or how omissions found after release are tracked.
The capability is described and the models are not. aiomics' ISO certificate scope describes a platform based on generative AI; the product compares sources, checks completeness and consistency, and returns structured, coded data with FHIR handoff. No model or model family, accuracy figure, evaluation method or update practice is published.
The design is outlined with no supplier named. aiomics states processing stays in EU data centers and that patient data does not train AI models, and points to its trust center for the list of processors. Its public pages name neither the company that hosts the platform nor the one that provides the generative models; the trust center may list both.
Named partners and customers, with results still to come. aiomics names MEDICLIN Soltau, MEDICLIN Fachklinik Breisach, MEDICLIN Donaueschingen and the Charité, where an independent scientific evaluation is underway with results to be published. It publishes no outcome figures yet, and says it agrees measures per deployment for time spent, documentation quality and economic effect.
Categorical commitments without a retention schedule. aiomics' security page states patient data is processed and stored only in data centers within the EU, is not used to train AI models, stays isolated per clinic tenant, and is handled under data minimization and pseudonymization, with processing on a GDPR Article 6 and 9 legal basis set by the clinic. Retention and deletion periods are not stated, and the application level C5 attestation is described as in preparation.
Outside the United States, the equivalent regime is documented. aiomics serves European hospitals and processes patient data on a GDPR Article 6 and 9 legal basis set by the clinic, only in the EU, under a data processing agreement listed in its trust center; HIPAA and business associate agreements do not apply. The agreement text itself is not posted.
A certification named with type, version, certifier, date and scope. aiomics' security page states it is certified to ISO/IEC 27001:2022 by TÜV NORD CERT, with a certificate dated 18 May 2026 covering the development, operation and maintenance of its generative AI platform, and links a trust center for current certifications and processors. The certificate itself may sit in that trust center, though nothing states whether it opens without a request. Its application level C5 attestation is in preparation.
No device position is published for the product sold today. aiomics drafts documentation and insurer correspondence for professional review and release, and the EU regimes in range are the Medical Device Regulation, if any function is intended to inform diagnosis or treatment, and the EU AI Act's obligations for AI systems used in healthcare. The company claims no classification under either.
A governance process with named elements, and no subgroup results yet. aiomics commissions an independent scientific evaluation with the Charité and states results will be published on completion; it offers each clinic an introduction service that includes structure for AI use and vendor assessment, and agrees evaluation measures per deployment covering time spent, documentation quality, economic effects, review effort, rework and the limits of the findings; evidence and its scope are provided for the clinic's own review. No bias or subgroup evaluation is published.
Mechanisms exist and nothing stands behind them yet. aiomics drafts are compared against their sources with omission checks, discrepancies between sources are flagged for the team to resolve against the original, and the site states that AI generated content can contain errors and omissions and must be reviewed and released by professionals before use. An independent evaluation with the Charité is underway, with publication promised. No error rate, warranty or remediation commitment is published.
Standards support with named deployments behind it. aiomics ingests speech, handwriting and existing documents (PDFs, scanned letters, printed reports) and returns structured, coded data to existing systems through FHIR based handoff, deployed at named MEDICLIN clinics. No hospital information system is named and no integration documentation is published.
Residency and isolation are stated, with the processing path left to the documentation. aiomics states all patient data is processed and stored only in EU data centers and stays isolated per clinic tenant; the data flows and protective measures are described in technical and organizational documents provided to the clinic, and its own application level C5 attestation is in preparation. The site describes no deployment option other than the hosted platform, and the processors are listed only in its trust center.
No price is published and the posture is discoverable in part. aiomics sells a platform to clinics with an introduction service, starting from a clearly scoped first use case, and frames value as time for patients, reliable documentation and revenue for care delivered, with measures agreed per deployment. Nothing states a price, unit of charge or basis.
Coverage is named with validation behind part of it: German rehabilitation and acute care clinics, across admissions, physician and rehabilitation discharge letters, patient questionnaires, case reviews with insurers (Falldialoge and Vorverfahren for Medizincontrolling), and billing evidence for private physician billing. Named MEDICLIN rehabilitation clinics support the rehabilitation setting; acute care validation awaits the Charité evaluation.
Alternatives to aiomics
Vendors in the same categories as aiomics whose graded profiles look most alike, with a line on what each product does.
Similar is not the same, so check that each one does the job you need. No vendor pays for placement.
Patients.app, from Granville Labs, finds a patient's records across other hospitals and practices and uses AI to screen them for a specific decision.
Wellsheet sells a Care Team Copilot that sits on top of the EHR and reads the existing chart rather than listening to the visit.
Carta Healthcare supplies software and clinical abstraction services for hospital registry teams.
Credo Health, based in Denver and led by founder and chief executive Carm Huntress, retrieves and assembles patient records for value based care.
Averbis is a Freiburg company that turns unstructured clinical documents, mostly in German, into structured data.
Layer Health is a Massachusetts Institute of Technology spin out, founded in 2023 and based in Boston, applying large language models to clinical chart review.
Ordered by how closely the graded profiles match across the fifteen axes, inside the same categories. See how each axis is graded in the methodology.
Pricing
Vendor-published figures are labeled as such. Figures labeled “Estimated” are derived from third-party sources and have not been confirmed by the vendor.
| Entry Price | Pricing Basis | BAA Tier | Implementation | Source |
|---|---|---|---|---|
|
Not published
|
Undisclosed. Sold to European rehabilitation and acute care hospitals, with a separate line for practices and telemedicine providers. | Not applicable. This is a European product with all processing in the EU; the governing instrument is a GDPR Article 28 data processing agreement rather than a business associate agreement. | Not published. The company positions its architecture as adapting to individual hospitals, departments and specialties rather than requiring workflow change, and describes fast integration, but states no fee structure either way. | Vendor Published |
No price, tier or pricing mechanism was located, so commercial transparency is Not Rated per the house convention rather than graded down. The published economic framing covers protecting revenue, increasing occupancy and relieving staff, which describes claimed value rather than cost.
Four things to establish. Which product you are buying, since the hospital platform and the practice and telemedicine assistant are separate lines and the second is described as still in pilot. What the pricing unit is, because a per bed, per clinician, per document or per case model behaves very differently in a rehabilitation hospital with long stays than in acute care. Whether the economic case travels, because reimbursement mechanics differ substantially between European health systems and a business case built on one national funding model should not be assumed to hold in another. And what happens on the regulatory path, since the company states it is working toward ISO 13485 and MDR alignment, so establish the timeline and whether any contractual commitment attaches to reaching it.
One item to ask for rather than negotiate: the independent evaluation underway at the Charité Institute for Medical Informatics. Ask when results are expected, what is being measured, and whether the buyer can see the protocol. A vendor that commissioned an independent academic study should be willing to share what it asked to be measured.