Energy & Manufacturing companies are rapidly adopting AI — predictive maintenance, GenAI assistants, RAG systems, agent-based automation, anomaly detection, optimization models — but most are held back by one foundational challenge:
AI cannot scale without a modern, governed, cloud-ready platform.
Frame’s AI Platform Implementation service builds the core infrastructure, governance, tooling, and automation needed to operationalize AI across the enterprise — safely, securely, and at scale — on Azure, AWS, GCP, and Databricks Lakehouse.
We combine cloud engineering, MLOps/LLMOps, security, and industrial domain expertise to deliver platforms that support real-time Operational Data Streams, enterprise knowledge sources, ML workloads, GenAI assistants, and the next generation of agentic systems.
A modern AI platform must do more than host models. It must unify and govern data at scale, enable secure deployment of ML and LLMs, integrate enterprise knowledge through RAG, automate pipelines and lifecycles, enforce security and Responsible AI controls, and support real-time decision-making — all while remaining cost-efficient and scalable.
We design and implement a scalable foundation for AI workloads with:
Architecture is tailored to your cloud environment, existing systems, and operational constraints.
We operationalize AI with production-grade automation across:
This creates a sustainable operating rhythm for AI across the enterprise.
To support GenAI use cases, we implement:
This allows GenAI assistants, copilots, and agents to deliver accurate, domain-aware responses.
AI requires stronger controls than traditional analytics.
We implement:
This ensures AI is safe, compliant, and aligned to operational risk profiles.
We configure and integrate:
This creates a cohesive ecosystem rather than a patchwork of tools.
We give organizations full visibility into:
The platform runs efficiently, predictably, and with continuous improvement.
With Frame’s AI Platform Implementation services, clients gain a production-ready foundation that allows AI to operate reliably at enterprise scale. Our platforms are designed to support real-time operational workloads, governed AI deployment, and continuous innovation without sacrificing security, safety, or cost control.
By combining proven architecture patterns, strong governance, and disciplined delivery, Frame helps organizations move beyond fragmented tooling to a cohesive AI platform that can support today’s analytics and GenAI needs while scaling confidently into future agentic systems.
We specialize in platforms capable of processing real-time Operational Data Streams from refineries, plants, and field assets.
Our governance frameworks reflect the realities of OT/IT integration, safety, cybersecurity, and compliance.
We architect AI platforms that leverage the strengths of each hyperscaler — while unifying data and AI workflows through Databricks or cloud-native ML services.
Our reusable templates, pipelines, governance patterns, and automation scripts compress implementation timelines from months to weeks.
Architecture, design, and governance are driven by Houston-based leaders; scalable engineering is supported by nearshore pods — delivering enterprise quality at a cost-smart run rate.
Designed for asset-intensive industries where real-time data, safety, and operational reliability are critical.
Platform implementation services that operationalize AI through secure, scalable data, tooling, and governance.
