A specialized electronic data capture platform for studies that need structured eCRFs, subject and visit management, data review, controlled changes, auditability, reporting and reproducible exports.
Our EDC platform is designed around the real study lifecycle: build the protocol structure, configure forms and visits, collect data, manage queries and validations, monitor quality, control changes and prepare analysis or publication-ready outputs.
This visual is an illustrative interface concept created for the Swasthit website. It is not a screenshot of another EDC vendor and should not be interpreted as a live product screenshot.
Missing data 14
Queries 37
Stable sites 8
Different studies need different levels of control and sophistication. The platform can be configured around the study's operational and governance requirements.
Forms, subjects, visits and structured data entry provide the foundation for study data capture.
The platform supports study structure, subjects, visits, forms, field-level data capture and operational data entry workflows.
Queries, validations, role-based access, reports and exports move the system beyond basic data entry.
Configure edit checks, data queries, role-based permissions, operational reports and controlled exports for routine study management.
Audit trail, electronic signatures, validation and controlled changes support higher-governance study workflows.
Capabilities include traceable changes, user attribution, time-stamped audit information, electronic signatures and controlled configuration changes.
Multi-study, multi-site, SSO, APIs and integrations support larger research operations.
Structure multiple studies and sites, integrate identity and external systems, and expose controlled APIs where required.
Central monitoring, data-quality signals and risk dashboards help teams focus review effort.
Surface missing data, unusual patterns, query trends, site-level signals and configurable risk indicators for centralized review.
Dataset freezing, reproducibility, provenance and publication-oriented exports support the final data lifecycle.
Freeze controlled datasets, preserve metadata and provenance, document transformations and generate repeatable analysis or publication exports.
CDISC/ODM, FHIR, APIs and standard terminology can connect the EDC ecosystem to other systems.
The architecture can support standards-based exchange and integration patterns; exact standard coverage depends on the implementation and project requirements.
AI-assisted review, anomaly detection and automated quality signals can augment data-management workflows.
AI can help prioritize records for review, identify unusual patterns and surface potential data-quality signals while keeping human review in the decision loop.
Capabilities such as role-based access, audit trails, electronic signatures, validation rules and controlled changes can support controlled research workflows. Regulatory suitability depends on the configured system, validation evidence, procedures, infrastructure and intended use.
Depending on the project, integration patterns can include APIs, structured data exchange and healthcare interoperability standards. Exact coverage is implementation-specific.
Share the protocol, CRF, workflow or data requirements. We can discuss the appropriate EDC, REDCap/eCRF or custom research technology approach.