What are the main implementation or deployment challenges you’ve encountered, and how have you addressed them?

The main implementation challenges we’ve encountered largely revolve around data management, infrastructure variability, and workflow integration-common barriers in healthcare AI deployments. In smaller neurology programs with limited IT capacity, the primary hurdle was securing seamless deployment without overwhelming local teams. To address this, we built modular data-ingestion pipelines that allow imaging data to be uploaded in controlled batches, supported by automated checksum validation and built-in de-identification. This approach minimized operational burden while maintaining compliance and data integrity.

In contrast, deployments in large academic medical centres introduced a different set of challenges, including navigating complex firewalls, diverse data repositories, and stringent patient data governance protocols. To meet these requirements, we developed standardized, version-controlled processing workflows that align with institutional policies and ensure consistent, reliable performance.

These solutions together have evolved into a scalable deployment playbook-one that not only meets today’s clinical and security demands but also prepares us for future expansion into real-time endovascular and procedural support.

What have you learned about what your customers need and how you shape your business model accordingly?

Through extensive collaboration with neuro specialists and over 350 clinician interactions across North America and Europe, we’ve learned that customers value three things above all: clinical relevance, seamless integration, and clarity. These insights shaped our approach from the start. Clinicians made it clear that even the most advanced AI is only useful if it fits naturally into their workflow. This reinforced our decision to build a lightweight, EHR-integrated SaaS platform that reduces friction between neuroradiology, vascular neurology, and neurosurgery teams rather than adding another layer of operational complexity.

We also learned from nursing teams and patients that clear, interpretable information is essential. Many patients struggle to understand traditional imaging results, which often increases anxiety and leads to unnecessary consultations. In response, we designed dynamic visualizations and transparent scoring that provide straightforward, non-invasive explanations early in the care pathway.

For hospitals and institutional buyers, priorities such as cost efficiency, improved resource utilization, and alignment with value-based care heavily influenced our hybrid pricing model and scalable deployment strategy. Ultimately, customer feedback has continuously shaped CARA into a clinically meaningful, operationally efficient, and financially aligned solution.

As you scale from a startup into a growth-phase company, how do you maintain innovation, agility and clinical focus?

As we scale from a startup into a growth-phase company, we maintain innovation, agility, and clinical focus by anchoring our growth strategy in structured, clinician-driven product development. Clinicians remain deeply embedded in our iterative cycles, ensuring every feature is shaped by real-world neurovascular workflows rather than abstract technical goals. Continuous feedback from nursing teams, care coordinators, and institutional partners creates a feedback ecosystem that keeps our roadmap responsive and clinically grounded.

Our platform is intentionally built on a modular architecture-spanning imaging analysis, non-invasive hemodynamic modelling, and clinical scoring-which allows each layer to evolve independently. This ensures we can rapidly deploy improvements or new capabilities without compromising reliability or disrupting existing workflows. Our SaaS delivery model further supports this agility, enabling seamless updates across diverse hospital environments.

To preserve scientific rigor, we invest in ongoing validation studies, collaborate with professional societies, and advance steadily toward regulatory clearances. Our commitment to transparent and interpretable AI keeps patient impact at the forefront, ensuring that as the company grows, clinical discipline and innovation scale in parallel.

What geographies or market segments are you prioritizing for expansion, and why?

Our expansion strategy prioritizes geographies and segments that maximize clinical impact, regulatory readiness, and pathway to scaled adoption. In the near term, the U.S. remains our primary focus-specifically leading academic medical centres and comprehensive stroke programs. These institutions combine high patient volumes with strong innovation cultures, making them ideal partners for clinical validation, rapid deployment, and early regulatory traction. Their influence within the broader healthcare ecosystem also helps accelerate downstream adoption across integrated delivery networks and community hospitals.

Beginning in Q3 2026, we plan to extend into key European markets, particularly regions with established AI frameworks, centralized health systems, and advanced neurovascular care capabilities. These systems offer strong research partnerships, progressive technology standards, and structured reimbursement pathways that support evidence generation and commercialization.

Beyond these core markets, our long-term growth follows a land-and-expand strategy across adjacent clinical verticals. Leveraging CARA’s modular, validated technology stack, we aim to expand into ischemic stroke prediction, cardiovascular risk modelling, and AI-assisted surgical guidance. These areas share similar challenges diagnostic complexity, fragmented data, and time-critical decision-making allowing us to scale with both high clinical relevance and operational efficiency.