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Pharma organization deals with data from various sources and effective data engineering is a critical stepping stone for successful operations. We transform raw data from multiple sources and turn them into usable formats and easily consumable data serving data scientists, AI/ML engineers and data consumers for building ML models, AI applications, perform advanced analytics for better decision making.
Our Solution
Circulants intelligent Data Management Product (iDMP) provides a scalable, governed foundation to integrate fragmented data, standardize it to industry frameworks, and enable trusted, analytics-ready insights.
Combining automated data pipelines, embedded governance, and AI-enabled intelligence, the solution accelerates decision-making, improves regulatory readiness, and empowers organizations to unlock greater value from data across the product lifecycle—from research and clinical development to commercialization.
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In large and globally spread pharma organizations, it is imperative to have a Data ecosystem that integrates best-of-breed, multi-vendor tools to build flexible data platforms serving subject matter experts, frontline sales team, data scientists, and developers. We deliver modern data engineering services in partnership with industry leaders help in modernizing your data ecosystem and be AI ready.
We do a deep dive into your current data landscape and assess from multiple perspectives to understand architecture, data quality, governance, analytics, operations, people & tools.
We utilize proven techniques, tools, fitment analysis and scoring models to identify gaps and create a highly customized maturity up-lift plan that meets your growing business needs.
We empower your business with strong data architecture and governance foundation that delivers secure, reliable, and discoverable data.
Our Data engineering experts create domain centric, cloud agnostic Unified Architecture blueprint, with well-defined policies, Master Data Management and Data Quality Frameworks for delivering trusted data across diversified teams.

Backed with years of experience building complex data pipelines for our pharma customers, we have the expertise to deliver reliable and automated data pipelines that autonomously orchestrates, handles ingestion from varied data sources, transforms (ETL, ELT) and moves data to the right storage destination.
Whether it is on-premise to cloud or cloud to cloud, we offer comprehensive Technology migration services to securely move data from source to destination without compromising data integrity and security with minimal business disruption.
We use advanced encryption standards (SSL/TLS/AES/RSA) and IAM policies to secure data in-transit.
We build and deliver production-grade, domain centric Data warehouses and lakes governed by a federated framework that delivers agility, flexibility and scalability for teams to build domain specific Data products for targeted analytics. Our approach enables delivery of real-time, optimized, trustworthy datasets for quicker rollouts of AI/ML models.
We offer AI driven DataOps Managed services with automation first approach to effectively operate your enterprise data platforms. Our DataOps experts leverage AI based Data observability toolkit to detect and fix any data issues before it impacts the business and maintain a healthy data pipeline to ensure seamless flow of trusted data across systems.
We understand that Data security and compliance is of paramount importance to pharma industry to safeguard sensitive organization and patient's data. Our capabilities and services help your organization to stay complaint, enforce security policies, safeguard intellectual property, and reduce cybersecurity risks
Our Data Visualization capabilities help your organization in transforming massive datasets into unified intelligence, enabling end users to discover key actionable insights effortlessly.
We leverage industry leading off-the-shelf visualization tools including Power BI, Tableau, Qlik to deliver interactive dashboards, enabling users to slice & dice to discover patterns & trends from multiple dimensions.
Circulants proven Data Quality framework leverages machine learning, anomaly detection, metadata analysis, and continuous monitoring to proactively identify and resolve data issues before they impact analytics or operations. The framework automatically profile datasets, detect schema drift, suggest remediation actions, and even learn from historical corrections to improve over time. This enables your organizations to move from reactive data cleansing to predictive quality management, enhancing trust in dashboards, AI models, regulatory reporting, and strategic decision-making.
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