Passionate, client-first thinking is at the core of what we do. Dive into our case studies to see how we approach each client with passion, dedication, and a focus on achieving real wins.
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App Modernization
Agentic AI
Manufacturing
Challenge
Rigid SAP HANA systems stalled real-time insights and ML adoption. The supply chain needed to break free from static ERP analytics and move to an AI-ready, cloud-native data foundation for predictive, scalable decision-making.
↑ 15%
Production Yeild
↑ 20%
Supply chain efficiency
↓ 10%
Delivery time
AI Development
Custom Software Development
Manufacturing
Challenge
Billions are lost each year to downtime that could have been prevented. The goal: make predictive analytics practical, fast, and operator-ready.
400%
Faster file ingestion speed
70%
Lower ML deployment cost
300%
Reduction in infra cost
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