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RIΛD

MLOps on AWS (SageMaker + API First Inference)

Capture web/mobile events through API Gateway, transform/enrich with Lambda, land in S3, and query via Glue/Athena with optional Redshift Serverless marts. Deployed with CloudFormation and governed by Control Tower for multi-brand or multi-region analytics.

Operationalize ML with SageMaker training, registry, and API-first inference deployment</p.

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Who it's for

Teams stuck in 'notebook-to-prod' limbo who need repeatable, governed ML delivery.

Sales Lifecycle

Discovery: use case, baseline, target KPI
POC: one model through full CI/CD to shadow
Pilot: canary to 5–10% traffic, monitoring
Scale: blue/green, rollback, cost/usage guardrails

Success Matrices

  • Lead time to deploy ↓ 60–80%
  • Inference latency SLOs met
  • Drift detection MTTR
  • Model performance monitoring

Prerequisites

Data access
Feature definitions
IAM permissions

Deliverables

  • ML pipelines (code + IaC)
  • API contracts
  • Monitoring setup
  • Operational playbooks
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