AI that understands GI

WE ARE

Expanding our reach across GI disease applications

We’re more than just breakthrough models. We operationalize the most advanced GI models through end-to-end solutions that fit into clinical practice and research workflows.

Our modular platform serves as the foundation fordelivering advanced models through a secure, interoperable API pipeline that integrates seamlessly into existing systems.

Our platform-centric approach enables Dova to partner with agility across domains, with any organization.

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DovaVision

Sharper Insights. Smarter Decisions.

DovaVision uses advanced AI to automate scoring and rapidly analyze Ulcerative Colitis (UC) disease severity from endoscopy videos.

Designed for both research and clinical trials, it ensures enriched, consistent, objective, and efficient evaluation of UC

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Granular Disease Evaluation

Quantify subtle variations in inflammation, ulceration, and other disease markers across different regions of the colon.

Repeatable Precision

Reduce inter-observer variability, improving analysis consistency and real-world decision-making

Deep Feature Mapping

Analyze disease features that underpin scoring, enhancing precision and transparency of disease grading.

Dynamic Frame-level Analysis

Generate dynamic severity analysis across the full procedure —available as raw data for further analysis and intuitive visual outputs.

FOR CLINICAL TRIALS

Reliable AI for Smarter Clinical Trials

Detect nuanced changes in disease activity

Proactively ensure data quality and consistency

Scale without increasing manual workload

Standardized, deterministic scoring you can trust

WE ARE

Visual data that moves discovery forward

DovaVision unlocks deeper biological and therapeutic insights from endoscopic video, using explainable AI to surface subtle changes and hidden disease signals.

Detect subtle shifts. Uncover hidden patterns.

DovaVision’s explainable AI identifies nuanced biological and procedural signals from endoscopic data—offering new layers of insight into drug response, disease progression, and therapeutic impact.

Quantify treatment effects with objective AI endpoints.

Support biomarker discovery with visual and functional data generated from video-based scoring. DovaVision can support surrogate endpoints and enhance exploratory analyses.

Quantify response trajectories over time.

DovaVision enables consistent scoring across visits allowing researchers to monitor disease progression or therapeutic response with objective, reproducible endpoints over time. Ideal for longitudinal analysis, outcomes-based validation, and identifying early signals of efficacy.

Integrate visual data with multi-omic profiles

Pair DovaVision’s imaging biomarkers with other data sets such as genomic, transcriptomic, and clinical data to explore disease pathways, discover new biomarkers, and personalize treatments.

Advancing non-invasive precision for IBD monitoring

DovaSound

DovaSound is an AI-powered product currently under development, designed to enhance the clinical utility of intestinal ultrasound (IUS) for monitoring Inflammatory Bowel Disease (IBD). Built for both research and real-world care, DovaSound brings objectivity, automation, and clinical relevance to IUS—making it a smarter, more scalable alternative to traditional approaches.

Why DovaSound is the next step forward

DovaSound is being developed to meet rising demand for non-invasive, scalable tools that support earlier intervention, more frequent monitoring, and improved access across diverse patient populations. It is designed to reduce variability in interpretation, automate key measurements, and deliver standardized, unbiased insights—enabling faster decisions and greater precision in both care and research settings.

Built on proven foundations

DovaSound leverages Dova’s validated AI infrastructure—benefiting from prior development pathways, regulatory groundwork, and partnerships with global experts and institutions. Government-backed and KOL-supported, it’s positioned to accelerate adoption in both clinical and research environments.