AI Services Competency
Validated practice area covering AI services built on Amazon Bedrock and Amazon Bedrock AgentCore: agents that act through defined tools, answers grounded in the customer's own data, and people approving what matters.
- Validated
- AWS Partner
- On AWS's cycle
- 4 case studies
What it covers
AI that works inside the product, with people in control.
Our validated work is production AI: agents that act through the same tools as the product, answers grounded in each customer's own data, and a person approving anything consequential.
Agents on AgentCore
Agents that act through a defined set of tools, with an isolated session per user.
Grounded and guarded
Answers grounded in the customer's own data, with Amazon Bedrock Guardrails on content.
People approve
Ledger changes, assessments and refunds wait for a person, not the model.
Measured in production
Acceptance, accuracy and response times tracked from real use.
Validation criteria
What AWS assessed.
The criteria AWS assesses for this competency. Status is maintained in the CMS from AWS Partner Central.
How validation worksProduction workloads
AI products running on Amazon Bedrock with real users.
Customer references
Engagements with full architecture detail.
Technical review
AWS reviewed the agent and inference architecture.
Final validation
AWS's decision after the technical review.
Evidence
The engagements behind it.
These are the customer references submitted to AWS for this competency. Ask us about any of them.
~80%
Less sprint-planning effort
Seshira — engineering assistant
Sprint plans in under two minutes plus review, with 78% of recommendations accepted in production.
~60%
Less lesson-prep time
Karatux — AI teaching assistant
Curriculum answers from approved material, with assessment content reviewed by a teacher.
< 4 hrs
Per reconciliation batch
Mercado — AI reconciliation
Amazon Bedrock explains each discrepancy; a finance reviewer approves every ledger change.
< 1 min
First response
ShappX — support and recommendations
Two AgentCore agents grounded in live stock, handing refunds and order changes to a person.
Architecture
Patterns behind this practice.
Services
What we build it on.
- Bedrock
- Bedrock AgentCore
- Bedrock Guardrails
- Step Functions
- Lambda
- OpenSearch
Team on this practice
Applied AI runs out of the engineering bench, with the practice lead who built Seshira's agent layer.
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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.