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In progressAWS Competency

Machine Learning Competency

Submitted for applied AI that acts inside a product rather than alongside it — agent tooling, evaluation harnesses, and inference cost discipline.

Status
Under review
Submitted
July 2026
Decision
Expected Q4 2026
References
2 submitted

What it covers

Agents that act, not sidebars that suggest.

Our submission centres on production agentic systems — where the model invokes the same capabilities the interface does, and every action is auditable.

Agent tooling

Shared capability registries called by both the model and the UI.

Evaluation harnesses

Measurable agent behaviour, so model changes are testable rather than felt.

Inference discipline

Model selection and routing tuned against real cost and latency budgets.

Auditable actions

Every agent-invoked call recorded against the workspace history.

Validation criteria

What AWS assessed.

This competency is under AWS review. The criteria below reflect what has been submitted and what remains outstanding — we would rather show the real state than imply a badge we do not yet hold.

How validation works

Production workloads

Two AI-native products running on Bedrock with real users.

Submitted

Customer references

Seshira and Mercado submitted with architecture detail.

Submitted

Technical review

AWS solutions architect review scheduled for Q4.

Pending

Final validation

Decision expected before the end of the year.

Not started

Services

What we build it on.

  • Bedrock
  • Bedrock AgentCore
  • SageMaker
  • Lambda
  • DynamoDB
  • EventBridge

Team on this practice

Applied AI runs out of the engineering bench, with the practice lead who built Seshira's agent layer.

Work with this practice

Building AI that actually does something?

Discovery comes first — a short, bounded review that ends in an architecture, a scope, and a price. You keep the output either way.