Real-time Analytics · Risk Management
Cyntegrity needed a secure, globally available, cloud database that could combine clinical-trial data from multiple systems of record, preserve longitudinal context, satisfy data residency rules, and surface fraud and schedule risks quickly enough to improve trial quality and compliance.
Reported impact
Cyntegrity achieved 10x faster performance and 99.99% availability, reduced the maintenance burden from a projected 20 people to one, helped clients detect fraud and quality issues before studies failed, and used machine learning to forecast trial durations with near-two-week accuracy.
Cyntegrity runs its MyRBQM portal on MongoDB Atlas on Microsoft Azure so pharmaceutical sponsors and regulators can analyze global clinical-trial data in one secure, always-on environment. Clinical trial records from multiple source systems are stored as flexible documents with role-based access, multi-tenancy, and timestamped audit trails, while MongoDB Time Series Collections preserve longitudinal measurements so the platform can compare changes over time, predict study duration, and flag duplicate or anomalous submissions. Atlas's managed multi-cluster setup and backup integration give the company cloud resilience across regions, and real-time updates allow multiple researchers to collaborate without version-control issues or peak-time latency. This architecture also supports machine-learning workloads that detect fraud, estimate timelines, and surface compliance issues fast enough for sponsors and regulators to intervene before studies fail or budgets drift.
Clinical-trial records from customer systems flow into MongoDB Atlas on Azure, where timestamped observations are stored in time series collections, analyzed for anomalies and duplicate outcomes, and exposed in real time to researchers, sponsors, and regulators through the MyRBQM portal.
"Cyntegrity uses MongoDB Atlas on Azure for fast, scalable, and secure trial data management, enabling real-time insights, fraud detection, and accurate trial forecasting."
"Its portal has 99.99% availability and is so reliable that the company broadcasts its system status live on the website."
"To support longitudinal studies, MongoDB Time Series Collections ensure that every time-stamped customer data point is preserved with its original context."
"When they analyzed why it failed, MongoDB flagged 99% duplication between the outcomes from two medical centers."
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
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