- CareAxes workflows
- Live clinical encounters
- IVF / OB-GYN data
- Transactional care delivery
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Suja AI Suite — Clinical intelligence & documentationPurpose-built for fertility, IVF, and OB-GYN care, SUJA transforms care delivery data into an AI-ready research data layer with EMR-native trial workflows. Shaped by major pharma experience, it powers feasibility insight, cohort discovery, recruitment support, and real-world evidence.
SUJA's model does not bolt on a disconnected trials application. It extends the operational EMR into a parallel research intelligence layer supporting retrospective analysis, protocol matching, feasibility assessment, patient discovery, and AI-assisted exploration.
Grounded in real-world execution thinking shaped by prior work for a major global pharmaceutical environment, this model combines retrospective clinical analysis with proactive point-of-care recruitment support.
Identify high-volume practices and relevant patient populations.
Use historical data and trend analysis to estimate protocol support.
Match inclusion and exclusion criteria against available data.
Trigger workflow prompts during live encounters.
Route potentially eligible patients into structured review.
Track referrals, outcomes, and recruitment performance.
Fertility, IVF, and women's health generate some of the richest longitudinal journeys in healthcare. That makes them especially well suited for feasibility, trial recruitment, outcomes analysis, and real-world evidence.
IVF cycles, protocols, embryo development, outcomes, and repeat follow-up create strong research continuity.
Structured records, narrative notes, labs, and outcomes create deep research value.
Frequent touchpoints improve continuity and support ongoing evidence generation.
Supports protocol comparison, treatment effectiveness, and maternal-neonatal insights.
We are not simply building a trials module. We are building a continuous learning engine where care delivery and research intelligence strengthen one another over time. Every IVF cycle, protocol variation, patient interaction, and clinical outcome contributes to a research-ready environment that can improve recruitment, generate evidence, and support future clinical decisions.
Normalize and structure clinical content for research workflows.
Use LLM-driven exploration and protocol logic to accelerate candidate discovery.
Estimate likely patient availability and protocol fit before launch.
Support identification of eligible patients during live encounters.
Enable research analysis and real-world evidence across longitudinal data.
Whether the goal is feasibility analysis, cohort discovery, recruitment acceleration, or real-world evidence, SUJA helps transform operational clinical data into actionable research intelligence.
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