One study. Many disconnected sources.
Study documents
Protocols, plans, reports, and submission-ready content
Clinical systems
EDC, CTMS, eTMF, safety, and quality records
Policies & guidance
SOPs, regulations, standards, and control frameworks
Teams & partners
Sites, CROs, vendors, and specialist knowledge
Manual reconciliation required
Specialist review
Relies on scarce expertise
Search → interpret → compare → validate → draft → route for approval
Rework
RFI exposure
Submission delays
01
Evidence-Backed Intelligence
Every validation and compliance finding is tied to source evidence. If a finding cannot be substantiated against the source material, it is excluded rather than presented as fact.
02
Human Oversight
AI generates recommendations, findings, and drafts for human review, approval, editing, or rejection. Critical clinical and regulatory decisions remain with qualified professionals.
03
Configurable Governance
Validation rules, compliance checks, and country-specific templates can be managed through configuration, allowing the platform to adapt as requirements change without rebuilding core logic.
04
Complete Traceability
Actions, AI recommendations, user decisions, and document versions can be logged to support accountable and inspection-ready workflows.
05
Connected Study Intelligence
Bring together study and operational data through an integrated intelligence layer rather than forcing teams to work across disconnected workflows.
On time documentation completion
Reduced administrative effort
Reduced rework cost
Staff productivity
What is clinical trial intelligence?
How can AI agents improve clinical trial workflows?
Does elsai replace clinical or regulatory teams?
How does elsai govern AI agents in clinical research?
Who should use Clinical Study Intelligence?
