AWS Infrastructure for AI Workloads
Design, deploy and optimize infrastructure on AWS for your AI products — production-ready, automated, with predictable unit economics.
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AWS Infrastructure for AI Workloads
You're building with AI — we make sure the foundation doesn't fail you. Most AI products fail at the infrastructure layer, not the model layer.
- Architecture design and review for AI workloads on AWS
- AWS Bedrock and SageMaker deployment and configuration
- VPC, networking, and security posture aligned to production requirements
- Cost-aware compute selection matched to your workload
- Infrastructure as Code (Terraform/CDK) — nothing lives only in a console
AI Unit Economics
What is your AI actually costing you per user, per feature, per workflow? We build the visibility and the optimization strategy. Grounded in AWS CUR and Bedrock cost data.
- Token cost attribution by feature, user segment, or workflow
- AWS CUR analysis and Bedrock cost data instrumentation
- Model right-sizing — matching model capability to task cost
- Spend anomaly detection and budget guardrails
- FinOps reporting that ties AI spend to product outcomes
Implementation & Integration
We don't hand over a document. We build it with you — from architecture through deployment on AWS. Clean, production-ready, not just a proof of concept.
- Hands-on build alongside your engineering team
- Integration with existing AWS accounts, CI/CD, and observability stacks
- Deployment to production with runbooks and operational handover
- Knowledge transfer so your team owns what we build
Ready to build on a foundation that lasts?
Book a 30-minute call with Pratik to discuss your AI infrastructure needs. No pressure, no sales pitch — just an honest conversation about what would actually help.
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