Designed to support the scale, complexity, and performance demands of Energy and Industrial operations.

Databricks is a leading Data and AI platform built on the Lakehouse architecture, unifying data engineering, analytics, machine learning, and AI on a single, open platform. It enables organizations to move quickly from data ingestion to production-grade analytics and AI while maintaining enterprise-scale performance, security, and governance.

Designed to operate across all major cloud platforms, Databricks provides a consistent foundation for modern analytics and AI regardless of where data resides. This flexibility allows organizations to modernize data estates, operationalize AI, and drive measurable business outcomes at scale.

Frame delivers agentic AI and intelligent data workloads on Databricks to drive measurable business outcomes.

Frame and Databricks are aligned around turning complex operational data into real business value. Frame brings deep Energy and Industrial expertise and a Databricks-first delivery approach to help clients move beyond experimentation and into production, supporting initiatives such as operational efficiency, predictive insights, and AI adoption.

As a Databricks Consulting and Systems Integrator partner, Frame works closely with Databricks field teams to co-sell and co-deliver solutions across Energy and Industrial clients. Our local delivery model and repeatable accelerators enable faster implementations, reduced risk, and long-term success on the Databricks platform across cloud environments.

Designed to meet the demands of Energy and Industrial operations

Microsoft’s deep engagement with Energy, Industrial, and Manufacturing organizations has shaped its data and AI platforms around real operational challenges, from field systems and production environments to asset performance, safety, and emissions visibility. Across Azure, Copilot, and the broader Microsoft AI ecosystem, these platforms are built to support complex, mission-critical workloads at industrial scale.

Together, these capabilities provide organizations with a flexible, secure foundation to support a wide range of use cases, including drilling optimization, predictive maintenance, OT and IT convergence, enterprise data platforms, Copilot-enabled workflows, and agentic AI solutions that automate and enhance decision-making across the organization.

Frame brings proven, real-world expertise on Azure.

Frame’s teams have extensive experience architecting and delivering Microsoft-based data and AI solutions for some of the world’s largest Energy and Industrial companies. Our deep understanding of Microsoft Azure, Copilot, and AI design patterns enables us to build intelligent data platforms and agentic AI solutions that accelerate time to value, improve operational outcomes, and ensure long-term reliability for mission-critical environments.

SAP serves as the digital core for Energy and Industrial operations.

SAP underpins mission-critical business processes across finance, supply chain, asset management, and operations for Energy and Industrial organizations. As companies adopt S/4HANA and embrace clean core principles, SAP is increasingly used as the trusted system of record while advanced analytics, machine learning, and AI workloads are handled outside the core ERP to preserve stability, performance, and upgradeability.

SAP data is extended into Databricks to enable large-scale analytics and AI-driven insights without disrupting transactional systems. This architecture allows organizations to apply advanced analytics and AI to SAP data for use cases such as predictive maintenance, operational forecasting, supply chain optimization, and enterprise-wide reporting, while keeping SAP focused on core business execution.

Frame brings proven expertise extending SAP with Databricks.

Frame’s teams bring deep experience across SAP landscapes, enterprise data platforms, and Databricks-based analytics and AI solutions. With the recent release of Databricks on SAP Business Data Cloud, organizations now have a modern, supported architecture to extend SAP data into large-scale analytics and AI workloads without impacting core ERP operations.

Our architects are prepared to design and implement these patterns by applying proven data engineering, platform architecture, and clean core principles. This approach allows clients to move forward confidently with SAP analytics and AI initiatives, aligned to long-term SAP modernization strategies and production-grade data platform best practices.

Designed for asset-intensive operations requiring scale, resilience, and operational flexibility.

AWS provides a broad and mature cloud platform that supports the full spectrum of data, analytics, and AI needs for Energy, Industrial, and Manufacturing organizations. From large-scale data ingestion and storage to advanced analytics, machine learning, and real-time processing, AWS is built to support complex, distributed workloads across operational and enterprise environments.

These capabilities enable organizations to build flexible, secure data platforms that support use cases such as predictive maintenance, asset optimization, supply chain analytics, digital twins, and AI-driven decision support. AWS’s breadth of services and global scale allow teams to architect solutions that align to performance, resilience, and cost requirements across diverse operational footprints.

Frame brings delivery-ready expertise across AWS data and AI platforms.

Frame’s teams bring strong experience designing and delivering data and AI solutions on AWS for complex enterprise environments. Our architects understand how to apply AWS-native data services, Databricks on AWS, and AI capabilities to build scalable, production-ready platforms that accelerate time to value and support long-term operational reliability for Energy and Industrial workloads.