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A Fortune 10 global medical device manufacturer stood at a critical inflection point. As its portfolio of devices expanded and its global footprint grew, the organization’s research and development teams were generating unprecedented volumes of data—clinical trial results, laboratory insights, device telemetry, and regulatory submissions from markets around the world.
Yet, despite being rich in data, the organization struggled to turn information into intelligence.
Years of organic growth and acquisitions had left behind a complex web of legacy systems. Data lived in silos, fragmented across platforms that were never designed to work together. Researchers lacked a unified view of insights. Regulatory teams spent countless hours manually compiling reports. Scaling infrastructure to support real-time analytics and AI-driven innovation felt increasingly out of reach.
The organization knew the future of medical device innovation would be driven by artificial intelligence, advanced analytics, and cloud-native platforms. But before AI could deliver value, the data foundation itself needed a fundamental transformation.
That realization led the client to partner with Birlasoft.
Rather than approaching the engagement as a traditional data modernization effort, Birlasoft worked with the client to reimagine the role of data in R&D—envisioning a connected, intelligent ecosystem that could power innovation, ensure compliance, and scale globally.
The Problem
- Data Silos: Critical research data was dispersed across clinical trial systems, laboratory databases, device telemetry platforms, and external regulatory sources, making it difficult to derive end-to-end insights
- Scalability Challenges: Legacy infrastructure could not support the rapidly growing volume of clinical data, post-market feedback, and global regulatory information
- Data Quality and Consistency Issues: Manual integrations and inconsistent standards introduced errors and variability, reducing trust in analytics and AI models
- Regulatory Complexity: Managing sensitive patient and device data required strict adherence to HIPAA, GDPR, and FDA regulations, without a unified governance framework
These challenges not only slowed research and development but also limited the organization’s ability to adopt AI at scale.
The Transformation
Birlasoft began the transformation by addressing the foundation: data unification. The goal was to break down silos and create a single, intelligent source of truth for R&D.
A cloud-native, AI-powered data lake was designed to ingest and harmonize both structured and unstructured data from across the enterprise. Clinical trial data, lab systems, device telemetry, and regulatory inputs were integrated into a centralized platform that supports advanced analytics and real-time insights.
AI played a critical role from the outset. Intelligent data integration and harmonization ensured that disparate datasets aligned to common standards, eliminating inconsistencies that had previously undermined analytics accuracy. What once required extensive manual intervention became automated, repeatable, and reliable.
Scalability followed naturally. By leveraging elastic cloud infrastructure, the platform could seamlessly scale to meet global demand—supporting new devices, expanded trials, and additional geographies without performance constraints. Researchers across regions can now collaborate using a single trusted data foundation.
Governance and compliance, previously seen as barriers to speed, were embedded directly into the platform. AI-driven data validation, cleansing, and standardization ensured high-quality data while enforcing regulatory controls. Sensitive health and device data were managed securely, meeting global compliance requirements without slowing innovation.
With a robust data foundation in place, the focus shifted to generating insights and accelerating. Generative AI models and advanced analytics were embedded directly into the data lake. Researchers gained access to predictive modelling, intelligent visualizations, and faster discovery workflows—allowing them to explore hypotheses, identify patterns, and make informed decisions with confidence
AI was no longer an experimental add-on; it became a core capability powering everyday R&D activities.
The Impact
The transformation delivered measurable, enterprise-wide outcomes across innovation, efficiency, and compliance.
- 50% improvement in regulatory reporting timelines, significantly reducing manual effort and improving audit readiness
- 20% reduction in device discovery and development cycles, enabling faster go-to-market strategies
- 240K+ adverse events integrated and analysed through AI-powered safety surveillance, strengthening post-market monitoring
- $2 million in annual operational cost savings achieved through infrastructure optimization and automation
- Over 85% automation in code conversion and 50% faster dataset generation, dramatically improving R&D agility
A scalable innovation platform ready to support new device categories, research domains, and global expansion
The Outcome
What began as a data modernization initiative evolved into a strategic transformation of the client’s R&D ecosystem. The organization now operates on a unified, intelligent platform where data flows seamlessly, AI accelerates discovery, and compliance is built in by design.
By embedding generative AI, advanced analytics, and cloud-native scalability at the core of its R&D strategy, the client repositioned itself as a leader in data-driven medical device innovation.
Through this partnership, Birlasoft enabled more than just operational improvement—it helped create an R&D environment that is faster, smarter, and future-ready, empowering the next generation of healthcare technology.
