Sold by: New Math Data
AI workload migration from Azure to AWS, purpose-built for multi-tenant environments where a generic lift-and-shift won't hold up.
Overview
Multi-tenant AI platforms on Azure face compounding costs across LLM calls, data storage, and vector infrastructure. Migration to AWS is a meaningful opportunity to reduce spend while improving performance and architecture. New Math brings technical depth in both Azure and AWS environments, and the regulated industry experience to move fast without cutting corners on compliance.
- TCO and feasibility assessment comparing Azure and AWS costs
- AWS target architecture design with DynamoDB and S3 Vectors
- Full migration of AI workloads, models, pipelines, integrations, and data stores from Azure to AWS
- Phased cutover designed for multi-tenant environments
- Workflow optimization and operational cost reporting
Key Benefits:
- Compounding cost reduction across LLM, data store, and vector infrastructure
- Migration designed for multi-tenant realities, not a generic lift-and-shift
- Proven delivery speed in regulated environments
Best For:
Multi-tenant organizations running AI workloads on Azure using Cosmos DB and external OpenAI or Anthropic API calls, where cost or performance pressure is driving migration consideration.
Timeline: 8 to 12 weeks. Pricing: Scoped per engagement. Contact us.
Highlights
- Re-architecting across LLM, data store, and vector layer delivers compounding cost savings
- Designed for multi-tenant environments, not adapted from single-tenant playbooks
- Proven delivery speed to production for AI and agentic use cases in regulated industries
Details
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