Healthcare
Serving private healthcare centers nationwide
Progress notes, discharge summaries, referrals, and prescriptions written by hand or dictated into systems that do not integrate with the EHR. Physician time the patient never receives.
Incoming calls and messages classified by admissions staff without system support. Real emergencies mixed with schedulable consultations — wrong priorities.
Gaps from late cancellations, patients mis-assigned to the wrong specialist, dead time between appointments. Real utilization is not maximized.
Chronic or post-procedure patients without automated reminders or check-ins. Complications are detected late because the patient does not call — because no one gave them reason to.
01
The system listens to the consultation (with patient consent) or receives a natural language dictation and automatically generates the structured clinical note, report, and EHR orders. The physician reviews and signs — without transcribing.
What changes
Documentation time per consultation reduced 60-75%. Structural quality of the record improved for coding and billing.
02
An assistant that receives incoming calls, chats, and messages, classifies the reason for contact, assesses urgency against the center's protocols, and assigns to the correct resource: emergency, scheduled appointment, nursing, or information. No wait, no misclassification.
What changes
Admissions time per contact cut in half. Urgent referrals correctly prioritized. Admissions staff freed for in-person care.
03
A model that predicts cancellations 48-72 hours ahead and proactively fills from the waiting list. It also detects under-utilized slots from poor appointment-type assignment and recommends redistribution.
What changes
Schedule occupancy rises 8-15 points. Dead time between appointments reduced. Shorter waiting list without adding headcount.
04
Post-consultation, post-procedure, and chronic care follow-up protocols: reminders, symptom check-ins via chat or app, alerts to the clinical team if the patient reports warning signs. Everything logged in the EHR.
What changes
Complications detected earlier — fewer avoidable emergencies and better therapeutic adherence. Patient NPS rises from the perception of active follow-up.
05
Models identifying patients with high probability of decompensation, adherence decline, or upcoming review needs — on data already in the EHR. The nursing and family medicine team acts before the patient enters a crisis.
What changes
Avoidable readmissions and emergencies reduced in the monitored cohort. Better clinical outcomes documentable for quality audits.
2-3 weeks
Audit of administrative processes and care flows. We identify the 2-3 cases where AI frees the most clinical time with the least implementation friction.
8-12 weeks
The two fastest-ROI cases in most centers: assisted documentation and incoming contact classification.
5-8 months
For centers and groups wanting AI consolidated across all operations: documentation, triage, scheduling, follow-up, and chronic analytics.
Compliance is a design constraint. All projects are developed under signed data processing agreements, with data stored in EU infrastructure, no use for retraining general models, and role-based access segregated by clinical role. The center's DPO participates from the first phase.
The physician reviews, corrects, and signs — that is what carries legal weight. What AI does is eliminate transcription and structuring time. Clinical responsibility and signature remain with the professional.
We work with the leading platforms in the market via HL7/FHIR or API. The initial diagnosis validates the technical integration — if there are limitations we identify them upfront, not after starting.
Diagnosis: €5k-€10k. Pilot documentation + triage: €30k-€60k depending on number of specialties and centers. Full platform: €90k-€180k over several months. Recovered clinical hours translate into care capacity or reduced overtime — and that is the ROI.
Adoption depends on interface design and the system delivering value from day one. That is why we start with small pilots — one specialty, one shift — validate that documentation quality meets the physician's expectations, then scale with internal clinical endorsement.