AI-powered clinical trial management that eliminates the delays and cost overruns that haunt every CRO engagement — from site startup through TMF closeout.
The average Phase III trial runs 30% over budget and six months late. Behind every overspend is the same pattern: poor site selection, reactive monitoring, and a TMF left until the last minute.
Analysed 14 active sites against 3-year enrollment history, screen failure rates, and current patient pipeline. Three sites require immediate attention:
Across 14 sites, Leaf AI has identified 23 open protocol deviations and 147 outstanding data queries. Items material to the interim analysis:
Critical path item: Site 04 has 34 unresolved efficacy endpoint queries dating >21 days. At current resolution velocity, 11 will remain open at data cut. EDC · Medidata Recommend SDV escalation this week.
Overall TMF completeness: 74% against DIA Reference Model. At current completion velocity, projected completeness at inspection date is 81% — below the recommended 95% threshold.
| Zone | Complete | Progress | Status |
|---|---|---|---|
| 01 — Trial Management | 92% | On Track | |
| 04 — Site Management | 61% | At Risk | |
| 07 — IP & Blinding | 43% | Critical | |
| 08 — Safety Reporting | 88% | On Track |
Most trials are already behind before the sponsor realises it. Leaf AI is designed to be deployed fast — so you can surface risk signals, replan, and intervene while there is still time to change the outcome.
Continuous analysis across enrollment velocity, site performance, protocol deviations, data quality, and TMF completeness. Every signal is scored, prioritised, and surfaced in real time.
Receive daily risk digests, intervention recommendations, and predictive cost impact estimates. Your team acts weeks earlier — before delays compound into budget overruns.
Leaf AI analyses your clinical programme the way your most experienced CRA would — systematically, continuously, and with complete visibility across every site. Talk to our team →
Score candidate sites against enrollment history, investigator track record, regulatory compliance, and patient population data. Pick winners before SIV spend begins.
Replace periodic CRA visits with live risk scoring. Leaf AI flags data quality issues, protocol deviations, and enrollment anomalies the moment they appear in your EDC.
Real-time completeness scores against the DIA Reference Model. Every missing document, metadata gap, and misclassified artifact is flagged with owner-level remediation tasks — weeks before your inspection.
Automate the coordination of site activation tasks — IRB submissions, contract execution, lab setup, and investigator training — with intelligent deadline tracking and blocker alerts.
Model the cost impact of emerging risks in real time. Translate site delays, query resolution rates, and enrollment shortfalls into projected budget variance before they crystallise.
Unify signals from your CTMS, EDC, eTMF, safety, and finance systems into a single intelligence layer. Ask anything about your trial in natural language and get an answer in seconds.
AI-powered clinical trial management uses machine learning to continuously analyse data from the CTMS, EDC, eTMF, and site systems — surfacing risks, predicting delays, and recommending interventions before small problems compound into costly overruns. Leaf AI replaces reactive, spreadsheet-driven oversight with live intelligence across every stage of your trial.
Leaf AI gives sponsors a real-time view of CRO performance across sites, data quality, TMF completeness, and budget trajectory — independently of what the CRO reports. Sponsors can identify emerging risks earlier, challenge scope changes with data, and avoid the information asymmetry that drives cost overruns in most CRO engagements.
Leaf AI continuously maps your eTMF content against the DIA Reference Model, scoring completeness by zone, section, and artifact type. It flags missing documents, metadata errors, misclassified files, and completeness velocity so you can course-correct weeks or months before an inspection — not in the final days when remediation is expensive and stressful.
No — Leaf AI amplifies your team. CRAs using Leaf AI spend less time on routine data review and more time on meaningful site intervention. Sponsors gain independent oversight without additional headcount. The result is the same team delivering better outcomes with fewer surprises and lower overall trial cost.
See how Leaf AI's Clinical Intelligence gives your team continuous, proactive oversight — from first site activation to final inspection.