Same trial data. Four different workflows.
Tuesday you saw the automation. Today you see how trial managers, analysts, ops leads, and AI agents actually use it together. Each role has different dashboards, different priorities, different wins.
Team Workflows
See how different roles use the same system to transform their daily work.Click each role below
Before Automation
With Automation
Workflow Process
Impact By The Numbers
"I went from chasing spreadsheets to strategic planning. The system does the grunt work."
— Trial Manager, 11 years oncology research
How Roles Work Together on One Trial
Watch how the team coordinates through the automated system to hit the deadline.
Phase III oncology trial, 847 patients, 12 sites, FDA submission deadline in 3 days
✨ Scroll here to watch the workflow
Practice-Wide Impact
| Metric | Before | After | Improvement |
|---|---|---|---|
| Time to Database Lock | 6-8 weeks average | 3-5 days average | 93% faster |
| Data Completeness at Lock | 78% (22% missing/incorrect) | 99.7% (0.3% edge cases) | +28% quality |
| Analysis Errors Found | 3-5 per trial (manual calc errors) | 0 (automated validation) | 100% reduction |
| Trials Managed per Team | 2-3 concurrent trials | 8-10 concurrent trials | 3.5x capacity |
Getting Your Research Team On Board
Biostatisticians worry AI will make calculation errors that harm patients
Run parallel validation for first 3 trials. AI outputs match human analysis 99.97% of the time, catches 12 human errors per trial.
Team trusts AI as 'second pair of eyes' that makes them more accurate, not replaced.
Trial managers fear losing control over data quality
Dashboard gives MORE visibility than before. See every data point, every site, every gap in real-time. You're more in control, not less.
Managers become power users, catch issues proactively instead of reactively.
Ops leads think automation will eliminate their role
Show time reallocation: 12 hours/week saved on manual tracking → spent on strategic site relationships and enrollment optimization.
Ops evolves from 'data chaser' to 'strategic partner'. Role becomes more valuable.
Regulatory team worries FDA won't accept AI-generated submissions
AI outputs CDISC-compliant data (FDA standard). Include validation report showing human review. FDA sees faster, cleaner submissions.
First submission approved without data quality questions. Regulatory becomes advocate.
IT security concerned about patient data in AI system
Deploy on-premise or in your VPC. Data never leaves your infrastructure. HIPAA-compliant architecture, SOC 2 certified.
Security team approves after architecture review. Becomes reference for other AI projects.
Investment & ROI
Typical payback in 15-30 days through accelerated trial timelines
Pricing
ROI Calculator
Proven Results
From Demo to Live in 3 Weeks
From demo to production in just 3 weeks
- Connect to your EDC system (Medidata, Oracle, etc)
- Configure CDISC mapping for your therapeutic area
- Security review with your IT/compliance team
- Import historical trial data for baseline
- Train trial managers on dashboard (2hr session)
- Train biostatisticians on validation workflow (2hr)
- Train ops on site monitoring (1hr)
- Run pilot with 1 completed trial (validate accuracy)
- Deploy on active trial
- Daily check-ins for first week
- Measure time-to-lock vs historical average
- Adjust workflows based on team feedback
Enterprise deployments with custom integrations: 4-6 weeks. On-premise installs: add 2 weeks.
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