Every successful AI initiative begins with a modern, trusted, and well-structured data estate.
Frame’s AI-Ready Data Estate Accelerator gives Energy & Industrial companies a fast, predictable, and secure path to modernizing data environments across Azure, AWS, Google Cloud, and Databricks—so they can unlock analytics, GenAI, and automation at scale.
Designed by practitioners who have delivered some of the industry’s most complex data transformations, Frame’s Data Estate Accelerator condenses months of groundwork into weeks and gives your teams a governed, scalable, cloud-optimized data foundation ready for AI. This allows us to deliver:
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Frame provides cloud-native, reusable ingestion and transformation patterns that:
This delivers a production-ready landing environment designed to scale across any cloud or Lakehouse platform.
Using cloud-native governance capabilities and Databricks Unity Catalog, our accelerator establishes:
Your business and technical teams gain clarity, trust, and visibility across every data flow.
Frame delivers pre-configured cost and capacity models for Azure, AWS, GCP, and Databricks, including:
Clients receive the financial transparency needed to adopt cloud and AI at scale without unexpected costs.
Frame brings engineering discipline and industrial pragmatism to data modernization. Our approach delivers production-ready data foundations that are governed, scalable, and built to support analytics, GenAI, and automation from day one.
Clients move quickly from fragmented data environments to a lakehouse-ready platform designed for long-term AI confidence—across any cloud or Databricks ecosystem.
We understand the realities of industrial data: OT/IT integrations, historians, SCADA, supply chain, refining, maintenance, and compliance-bound environments. Our accelerator is purpose-built for these challenges—messy data, legacy platforms, and the need for continuous operational uptime.
This is not a theoretical framework. It’s the culmination of two decades of delivering real-world data modernizations on Azure, AWS, GCP, and Databricks for some of the world’s most operationally complex industries.
What typically takes 6–12 months can be achieved in weeks—with stronger guardrails, higher confidence, and a dramatically accelerated path to AI readiness.
Frame builds AI-ready data foundations for industries where uptime, safety, and operational performance depend on trustworthy data at scale.
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A modern data foundation enables downstream solutions for analytics, machine learning, GenAI, and operational intelligence.
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