Company profile
Healthplus.ai
AI tools for medical and health challenges, focusing on surgical care.
- Category
- Healthcare AI
- Headquarters
- Amsterdam, North Holland
- Sells to
- Enterprise
- Business model
- Not stated
- Deployment
- Cloud / SaaS
- Pricing
- Not published
- Builds own models
- Yes
- Modalities
- Tabular
What Healthplus.ai does
Healthplus.ai provides artificial intelligence tools to help solve medical and health-related challenges. They partner with hospitals and other healthcare institutions to deliver innovative solutions. Their mission is to enable proactive surgical care through personalized complication predictions for over 50 million patients annually by 2029, aiming for complication-free surgeries to be the standard. They build long-term relationships with partners to unlock intelligence from their data. Their team combines clinical expertise with technical excellence, including physicians, data scientists, and healthcare IT specialists.
Products
- PERISCOPEAn AI-powered clinical decision-support system that predicts post-operative infection risk by analyzing patient data directly in the Electronic Health Record (EHR). It provides 7-day and 30-day risk predictions immediately after surgery, along with top contributing factors, to help surgical teams prioritize follow-up care and make faster, more confident decisions. It is a CE-marked Class IIa medical device under EU MDR and integrates seamlessly into existing EHR systems like Epic and HiX.
Key capabilities
- Predicts post-operative infection risk
- Integrates directly into EHR (Electronic Health Record)
- Provides 7-day and 30-day risk predictions
- Identifies top contributing factors for risk
- Supports clinical decision-making
- CE-marked medical device (EU MDR Class IIa)
- Analyzes pre- and intra-operative patient data
- Processes approximately 50 clinical parameters
- Continuously validated and monitored
- Calibrated to hospital and surgical specialty
- No additional data entry required
- Seamless integration with Epic and HiX
Use cases
- Predicting post-operative infection risk
- Prioritizing follow-up care for surgical patients
- Earlier identification of high-risk patients
- Enabling proactive care decisions
- More efficient resource allocation in hospitals
- Safer and more confident discharge planning for low-risk patients
- Reducing post-operative infection-related costs and hospital stays
- Improving surgical outcomes
AI approach
Healthplus.ai provides AI tools to predict post-operative infection risk in hospitals. Their PERISCOPE® system analyzes approximately 50 clinical parameters from patient EHRs (demographics, comorbidities, vital signs, biomarkers) to generate a risk assessment with a probability score and contributing factors. It is a clinical decision-support system, not a diagnostic tool, and aims to provide transparent, explainable insights.
Tech named: Artificial intelligence, Machine learning, Deep learning, Big data, Advanced analytics
Industries served
- Healthcare
- Hospitals
- Medical Centers
What it says sets it apart
- CE-marked medical device (EU MDR Class IIa)
- Direct integration into existing EHR systems (Epic, HiX) without workflow changes
- Validated and implemented at leading medical centers of excellence
- Backed by peer-reviewed clinical studies
- Meets ISO 13485 and ISO 27001 standards
- Provides transparent, explainable insights with top contributing factors
- Focus on proactive surgical care and personalized complication predictions
- Team combines clinical expertise with technical excellence
Funding rounds we track
Elevating Capital, LUMO Labs, ROM InWest, Pathena Venture Capital, Leistone
From the AI funding tracker — rounds as reported by the linked publications.
This profile was compiled from Healthplus.ai's own public pages in July 2026 and reflects what the company states about itself — not an endorsement or an independent audit of those claims. Facts are extracted with AI and filtered by an automated check that drops any named product, customer or certification missing from the source pages. Full method. Something out of date? Tell us.