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Testing
Education
Challenge
BI & Analytics
All Industries
Challenge
Every dashboard change depended on IT. Logic was duplicated across workbooks. Governance was inconsistent.
60%
Reduction in development turnaround time
40%
Decrease in support ticket
75%
Reuse standardized semantic Layer
Artificial Intelligence
Custom Software Development
Pharma & Life Sciences
Challenge
Manual, error-prone processes delayed patient-to-trial matching, leading to missed enrollments, slower timelines, and underutilized clinical programs.
40%
Reduction in Patient Matching Time
Real-Time
Predictions via AWS SageMaker + MolecularMatch
30%
Higher Enrollment Rates + Expanded Trial Access
Artificial Intelligence
Data Engineering
Pharma & Life Sciences
Challenge
Data inconsistencies, missing fields, and anomalies in trial data risked delays, rejections, and regulatory setbacks, threatening both revenue and reputation.
40%
AI Models Flagged and Corrected Data Errors
CDISC SDTM
Compliance for Faster Approvals
30%
Reduced Review Time + Legal/Regulatory Risk
Custom Software Development
Pharma & Life Sciences
Challenge
Oncology clinicians struggled to find and apply the right treatment guidelines amid a flood of evolving protocols and fragmented documentation. Customization across institutions added more complexity.
60%
Reduction in Guideline Lookup Time
Streamlined
Care Decisions
30%
Custom Pathways Aligned with Institutional Protocols
Artificial Intelligence
BI & Analytics
Pharma & Life Sciences
Challenge
Business users struggled to extract insights, relying heavily on IT to run reports and queries. This slowed decision-making and stalled response to market changes.
2.5x
Faster Business Decisions
NLP to SQL
for Self-Serve Reporting
Zero-code
Visualizations Drove Data Confidence Org-Wide
