A global CPG enterprise pursuing a multi-cloud AI strategy struggled with adopting latest GenAI capabilities due to proprietary solutions from multiple providers. Blackstraw implemented a cloud-agnostic, agent-based AI architecture that enabled the organisation to operate AI workloads seamlessly across various cloud providers. This reduced costs, supported scaling of AI assistance and enabled adoption of new AI technologies without repeated platform redesign.
As organizations adopt multi-cloud strategies to ensure business continuity, avoid vendor lock-in, and use top GenAI services, they often face challenges due to platforms that are closely tied to a single cloud ecosystem. These limitations make it hard to use services that are often exclusive to specific cloud providers. They also complicate hybrid deployments and increase the risk of long-term dependency.
The client needed an AI architecture that could operate across cloud environments, maintain centralized orchestration and governance, and allow for quick integration of new AI services without disrupting existing deployments. Blackstraw worked with the organization to design and implement a multi-cloud-ready agentic AI foundation that meets these goals.
Cloud-Agnostic Agentic AI Architecture: Designed a multi-cloud–ready platform supporting Google Cloud, Microsoft Azure, and AWS in both standalone and hybrid configurations.
Unified Agentic Orchestration and Governance: Established a centralized orchestration, governance, and knowledge layer that remained consistent across cloud environments.
Selective Consumption of Cloud-Native AI Services: Enabled the organization to integrate cloud-specific GenAI and AI services without architectural rework or platform fragmentation.
Hybrid AI Deployment Model: Implemented a hybrid architecture where AI orchestration and knowledge components operated alongside specialized AI services and advanced search technologies across clouds.
Reduced AI Operating Costs: Enabled cost optimization by allowing workloads to run on the most economical cloud environment.
Freedom from Vendor Lock-In: Preserved architectural portability and flexibility across cloud providers.
Faster Adoption of Emerging AI Technologies: Allowed new GenAI services and accelerators to be integrated without platform re-engineering.
Enterprise-Scale AI Enablement: Supported scaling of AI assistants and agentic workflows across multiple business units.
Resilient, Future-Ready AI Foundation: Delivered a robust multi-cloud AI architecture designed to evolve with changing enterprise and technology needs.
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