Breaking Down Data Silos with C3 AI Data Sharing

Accelerating secure, flexible, and scalable enterprise collaboration

By Rohit Kalmankar Senior Manager, AI Solution Architecture, C3 AI, and Vanessa Kemajou, Senior AI Solution Architect, C3 AI

As organizations become increasingly data driven, they face a major challenge: how to share data effectively, securely, and at scale. Whether enabling AI initiatives, developing real-time analytics, or collaborating with partners, businesses require a platform that:

• Enables seamless data exchange across teams, locations, and external stakeholders.
• Maintains security and regulatory compliance (e.g., GDPR, HIPAA, CCPA).
• Ensures governed, high-quality data is available in near real-time.
• Integrates effortlessly with cloud and on-premises data environments without requiring complex rewrites.

C3 AI Data Sharing addresses these challenges by combining robust data ingestion, model-driven architecture, and fine-tuned governance in a single, integrated platform. Think about the usual headaches: multiple versions of the same dataset, unclear ownership, and compliance worries. C3 AI Data Sharing eliminates those pain points by unifying data management, AI/ML pipelines, and sharing mechanisms under one pane of glass.

A Stable Foundation for Enterprise Data Sharing

Just like a stable CPU/GPU architecture provides a consistent instruction set so developers don't have to rewrite code for each new chip, the C3 AI Type System offers a stable data blueprint that shields your applications from constant schema changes. As a result, you can evolve and scale your data environment without breaking existing apps - driving faster innovation and reducing complexity across the enterprise.

Why C3 AI Data Sharing Stands Out

• Seamless integration with existing data sources and enterprise applications without rewriting entire data flows.
• Scalable design capable of handling complex, multi-tenant architectures.
• End-to-end AI platform approach that merges data sharing with analytics, drastically reducing time-to-insight.
• In parallel, emerging open protocols like Apache Iceberg provide ways to securely share data across different platforms. By leveraging many of the same fundamental principles - such as strong governance, open data formats, and role-based access - C3 AI's data-sharing features can coexist or even complement open approaches, ensuring customers have the flexibility to modernize and scale.

Below, we'll outline the fundamental technical components of C3 AI Data Sharing. We'll simplify this overview but also highlight some of the why behind each decision - why it's structured this way, and how it benefits C3 AI customers.

1. Data Ingestion & Virtualization

   How It Works:

   • Pre-built Connectors: C3 AI integrates with databases, ERP/CRM systems, IoT streaming sources, and more.
   • Implemented Data Virtualization: Minimizing latency and storage overhead by reducing redundant data copies with virtualization layers.
   • Domains for Structured Management: A domain in C3 AI organizes related data (e.g., sensor readings, customer records) into logical, secure groupings (e.g., customer records, sensor readings). This enables consistent, scalable, and secure sharing across applications.

   Example: Wind Turbine Monitoring

   A global manufacturing company manages wind turbines across multiple plants and needs to share data securely. Using C3 AI Data Sharing:

   • A central data lake domain stores raw turbine data (temperature, rotation speed, timestamps).
   • Applications like WindTurbine connects to the data lake domain to use the turbine data for predictive maintenance and analytics, such as monitoring trends over time including generator speed.
   • Governance is enforced: Internal teams (e.g., data scientists) have access to detailed data for analysis, while external partners (e.g., maintenance contractors) are granted limited, read-only access to specific data fields.

   Why It Matters:

   • Eliminates data fragmentation and silos.
   • Accelerates development cycles by directly referencing live data.
   • Maintains a single source of truth across systems.

2. Data Modeling & Catalog

   How It Works:

   • Standardized object model: The C3 AI Studio unifies schema for entities like customers, transactions, or IoT sensor data.
   • Comprehensive data catalog: Stores metadata such as lineage, quality metrics, and versioning info.

   Why It Matters:

   • Maintains consistency across business units.
   • Enhances discoverability and usability of data assets.

3. Security & Governance

   How It Works:

   • Role-based access control (RBAC): Limits visibility down to the row or field level.
   • Attribute-based controls: Enforces dynamic security rules (e.g., region-based restrictions).
   • Encryption and data masking: Protects sensitive information like PII or health records.

   Why It Matters:

   • Ensures compliance with global regulations (e.g., GDPR, HIPAA, CCPA)
   • Minimizes the risk of data leaks and unauthorized access.
   • Provides secure, tailored access to external or third-party partners.

4. Data Sharing & Collaboration

   How It Works:

   • Defined data packages: Curated datasets grouped for easy sharing.
   • Multiple access mechanisms: REST APIs, direct queries, or push-based access.
   • Automated entitlements: Ensures permissions update automatically and dynamically as roles change

   Why It Matters:

   • Accelerates data access for internal teams and partners.
   • Reduces administrative overhead for compliance management.
   • Simplifies cross-team collaboration with governed data packages.

5. Scaling and Extensibility

   How It Works:

   As businesses expand, the C3 AI Type System ensures extensibility and scalability without the need for major rework. Consider a global manufacturer:

   • Adding new plants: New facilities integrate seamlessly by mapping data sources to existing "Machine" and "SensorReading" types.
     • The C3 AI Data Integrator handles the ingestion pipelines, so every new plant data is immediately standardized under the same schema - no painstaking manual integrations.
   • Scaling data volumes: The platform auto-scales to handle billions of sensor readings per day, optimizing performance and costs.
     • The C3 Agentic AI Platform can automatically adjust resources based on real-time load, ensuring both optimal performance and cost savings.
     • Real-time or near real-time data flows remain governed by the same C3 AI Type System, ensuring consistent data quality and security across all plants.
   • Flexible data access: Internal teams get full data access, while external service providers receive only the necessary fields - enforced through role-based access.
     • Internal teams (maintenance, data science, executive dashboards) get the rich "Machine" and "SensorReading" data for predictive modeling or real-time analytics.
     • When new service providers come on board - or existing ones require additional metrics - the C3 AI Type System lets you easily extend or restrict what is shared, without re-coding or re-architecting the entire pipeline.
   • Unified governance: Every data event is logged, ensuring compliance across all regions and stakeholders.
     • This unified auditing framework scales automatically across all plants, sensors, and user groups, ensuring compliance with safety or privacy regulations globally.
     • If a region-specific regulation demands anonymizing certain sensor data, administrators can override the default transforms or apply specialized masking rules - again, without changing core application logic.

   Why It Matters:

   By uniting flexible, extensible data models with a robust, enterprise-grade infrastructure, C3 AI Data Sharing empowers manufacturers to rapidly onboard new equipment, adapt to growing data volumes, and collaborate securely across business units and partners. This architecture minimizes manual integration work, accelerates time-to-value, and ensures consistent governance as business requirements evolve.

How C3 AI Data Sharing Fits into the Bigger Picture

C3 AI Data Sharing is a cornerstone of the broader C3 Agentic AI Platform, supporting enterprise-wide AI and analytics initiatives:

• Integrated AI and advanced analytics: Shared data is instantly available for advanced analytics and AI modeling, eliminating conversion bottlenecks; this accelerates the path to production for machine learning use cases such as predictive maintenance, fraud detection, or personalized recommendations.
• Enterprise scalability: Handles massive workloads while maintaining governance and security; as data volumes grow, your data-sharing architecture auto-scales to accommodate new demands.
• Open yet secure: Supports both interoperability with open standards; technical teams can tackle complex customer requirements - from real-time ingestion to multi-level data sharing.

Ultimately, C3 AI Data Sharing underscores our commitment to enabling faster, more reliable data-driven decision making. While open data sharing protocols like Delta Sharing offer valuable interoperability, C3 AI extends beyond a single protocol - providing a comprehensive enterprise solution that includes ingestion, governance, AI/ML, and, of course, data sharing.

Why It Matters for Your Business

If your organization struggles with data silos, compliance headaches, or fragmented analytics pipelines, C3 AI Data Sharing can provide significant relief by:

• Unifying data sources across cloud, on-prem, and streaming environments.
• Reducing the operational burden by eliminating the need for custom integrations.
• Ensuring data quality, lineage, and security for both internal and external users.

By consolidating diverse data assets into a governed, AI-ready environment, C3 AI Data Sharing enables enterprises to focus on extracting insights rather than wrestling with infrastructure. With built-in scalability, security, and flexibility, it's the future-proof solution for modern data collaboration.

Learn more:

• C3 AI Products and Solutions: Explore our enterprise AI platform
• C3 AI Documentation: Dive deeper into the technical details of data ingestion, modeling, and governance
• Case Study: How Data Virtualization Futureproofs Your Digital Transformation
• Case Study: How C3 AI Quickly Built a Custom Database Connector for Fast Application Deployment

About the Authors

Rohit Kalmankar is a Senior Manager of AI Solution Architecture at C3 AI, bringing over a decade of experience in artificial intelligence, machine learning, and cloud computing. He specializes in designing scalable, secure enterprise AI solutions that drive digital transformation and unlock measurable business value. Rohit leads high-performing teams and advises global organizations on AI adoption, multi-cloud architecture, and Generative AI deployment strategies. His expertise spans predictive analytics, MLOps, and real-time data integration across AWS, GCP, and Azure. Committed to helping customers achieve cost-effective, high-performance solutions, Rohit contributes to thought leadership at C3 AI and plays a key role in shaping the future of Enterprise AI through solution design, technical leadership, and collaboration with engineering and executive teams.

Vanessa Kemajou is a Senior AI Solution Architect at C3 AI, leading the design and implementation of artificial intelligence solutions across industries with a focus on scalability, security and optimization. She holds a Ph.D. degree in Petroleum (Computational) Engineering from Texas A&M University and degrees in Chemical Engineering, Physics and Computer Science. Vanessa's decade-long expertise covers cloud computing as well as the development and design of real time digital computational systems. She serves as a trusted advisor and technical leader for customers on their digital transformation journey.