Finakis is the payment integrity layer between hospitals and health insurers. Every day the same reimbursement regulation is applied to thousands of claims, yet the rules live in PDFs, errors surface after payment, and the AI tools offered for the job are black boxes that no payer can audit.
Finakis turns regulation and policy terms into executable, versioned, auditable rules and reads clinical documents with our own in house medical language model built for claims. The two layers work together: the model finds the evidence, the rule engine decides what it means, and every finding is traceable to a regulatory provision and to the clinical document behind it.
One engine serves both sides of the claim. Hospitals get paid what they are entitled to, before submission, without rework or appeals. Insurers pay the right amount for care that was actually delivered, with a documented rationale for every decision and the decision itself staying with the insurer. The architecture is multi payer and multi country by design: public, private and complementary insurance on one engine, and a new country added as a regulation parser plus a rule corpus. In production with hospital groups in Türkiye.
What we bring to Horizon Europe consortia: regulatory compliance as code and regulatory change tracking; clinical document reading with evidence linking and a medical language model; explainable, auditable decision support with human oversight; a multi payer, multi country rule architecture; real world hospital and insurer environments in Türkiye. We join consortia as a work package contributor and use case provider, and we are open to leading an SME driven Eurostars project.
Health IT SME offering a rule engine that turns regulation into auditable rules, a medical language model for clinical documents, and hospital validation in Türkiye. Seeking Cluster 1 2027 consortia on trustworthy AI and health systems.
Consortium/Coordinator seeks Partners
Destination 3: HORIZON-HLTH-2027-02-DISEASE-01-two-stage: Innovative healthcare interventions for non-communicable diseases
Destination 4: HORIZON-HLTH-2027-01-CARE-02: Personalised approaches to reduce risks from Adverse Drug Reactions due to administration of multiple medications