AWS AI Competency
As an AWS Competency partner in Resilience and DevOps services, 10Pearls brings the same validated rigor to generative and agentic AI solutions across industries and diverse AWS environments.
What is the AWS AI Competency?
AWS AI Competency (formerly the AWS Generative AI Competency) is Amazon’s validation program to recognize partners with demonstrated expertise across generative AI and agentic AI. The combined AI expertise and deep platform knowledge make AWS AI Competency partners strong choices for planning, building, and scaling AI initiatives in AWS environments.
Partners with AWS AI Competency bring proven technical expertise and hands-on field experience using AI tools and implementing AI solutions in AWS environments. They have a proven track record of successful agentic and generative AI implementations across industries, and the capability to help organizations build and operationalize cutting-edge AI solutions on AWS.
Benefits of working with an AWS AI Competency Partner?
Working with an AWS AI Competency Partner means your AI initiative is delivered by a team whose generative and agentic AI expertise AWS has independently validated, so you reach production faster and with less delivery risk.
AWS-validated, not self-claimed
The competency badge is awarded after a rigorous technical review by AWS and is not a self-declared proof-of-expertise.
Deep AWS platform expertise
Fluency across Bedrock, SageMaker, and AgentCore, so solutions are built the AWS-recommended way from the beginning.
Broad generative and agentic AI capability
The capability spans both AI domains, typically backed by supporting architectural and data engineering capabilities.
Faster pilot-to-production
Organizations can rely on validated AI partners to move pilot projects to production quickly, with resilience and scalability built in.
Secure, governed, responsible AI
Partners use AWS-native guardrails, monitoring, and access control to deliver secure, well-governed, and responsible AI implementations.
One accountable team
A single accountable team across strategy, build, and run means better alignment, less friction, and faster delivery.
Confidently scale agentic and generative AI initiatives in your AWS environment
How is the AWS AI Competency earned?
Acquiring an AWS AI Competency Partner badge requires existing AWS partners to go through a rigorous 4-step process.
Eligibility
There are two different paths for eligibility for software and services companies. The latter must meet the minimum validation criteria for the services path – becoming an AWS Advanced Tier Services Partner.
Validation
Partners that meet the requirements and pass the technical review get an AWS AI Competency badge that they can display on their website. It must be maintained with periodic re-validation.
AWS technical review
AWS ensures that partners have relevant certifications, engineering, and AI capabilities, multiple production-stage projects, and alignment with the Well-Architected Framework.
Self-assessment
Partners seeking the AWS AI Competency may self-assess against validation checklists (VCLs) to ensure they meet the technical and experience requirements.
Our generative AI capabilities on AWS
Our generative AI consulting services and capabilities span from identifying use cases to post-deployment support, backed by hands-on experience building and deploying generative AI on AWS.
Enterprise AI readiness assessment
Conduct tailored assessments covering data architecture, AWS environments, and integration gaps.
Software Generative AI strategy & roadmap
Align GenAI strategy with business goals and operational realities for minimal adoption friction.
Data pipeline & governance readiness
Implement data architecture and governance using AWS-native tools including S3, Glue, and Lake Formation.
Foundation model selection & tuning
Select and fine-tune the right foundation models on Amazon Bedrock and SageMaker for your use case.
Multimodal generative AI development
Build multimodal GenAI solutions that work across multiple data types using the right foundation models.
Retrieval-augmented generation (RAG)
Enable contextually aware GenAI results and minimize hallucinations with Knowledge Bases and OpenSearch.
Generative AI lifecycle and MLOps
Streamline and automate lifecycle management for your GenAI solutions with SageMaker MLOps tools.
Generative AI system integration
Enhance scalability and reduce operational friction in GenAI solutions with API Gateway-driven integrations.
Secure AI deployment & compliance
Implement secure and well-governed GenAI solutions in AWS environments using Bedrock guardrails and IAM.
Our agentic AI capabilities
10Pearls offers agentic AI consulting services that help enterprises move seamlessly from pilot to production. We also build secure, well-governed agentic AI on AWS, systems that can act with minimal human intervention.
Agentic AI design & development
Build secure, compliant, and production-ready agents aligned to your workflows on Bedrock AgentCore.
Multi-agent orchestration on AWS
Orchestrate multiple agents that collaborate across complex workflows and tools in your AWS environment.
Human-in-the-loop agent systems
Deploy human-in-the-loop agentic systems with checkpoints for sensitive decisions in regulated AWS environments.
Agentic architecture assessment
Assess readiness and modernize existing architecture to support autonomous, production-grade AI agents.
AgentOps & agent infrastructure
Deploy, monitor, and scale production agents with AgentCore runtime, memory, and observability tooling.
Agent-ready data architecture
Prepare secure, well-governed data and context foundations that agents depend on to act accurately on AWS.
The AWS AI stack we deliver on
AI & machine learning
Amazon Bedrock, Amazon Bedrock Knowledge Bases, Amazon Lex, Amazon Polly, Amazon Transcribe, Amazon Rekognition
Data, storage & search
Amazon S3, Amazon RDS, Amazon OpenSearch Serverless
Compute
AWS Lambda, AWS Fargate
Integration & events
Amazon API Gateway, Amazon EventBridge, Amazon SNS
Security & Identity
Amazon Cognito, AWS WAF
Observability
Amazon CloudWatch
Communications & contact center
Amazon Connect, Amazon Chime SDK
Agentic AI
Amazon Bedrock AgentCore
How we deliver
Each generative and agentic AI engagement is unique and may require a different approach, but a few steps present in all engagements are:
Development
We move to production-grade development, integration, and deployment, conducting thorough live testing and making configuration and orchestration changes in the operational environment.
Assessment
A comprehensive infrastructure and data architecture assessment helps us identify configuration gaps and map dependencies. It’s critical for an integration plan and scalable AI deployment.
Design
We design the solution on the most relevant AWS services and build a proof of concept. From scalability of GenAI solutions to agentic permissions, critical challenges are identified and addressed at this stage.
Discovery
We discuss your overarching business and operational goals you wish to achieve with the generative or agentic solutions. We also identify high-impact use cases and plan the roadmap.
Monitoring
We use AWS-native observability tools, monitor performance and agent behavior, and establish a feedback loop for ongoing improvement. The models and solutions are also monitored for drift.
Proof of our AI delivery on AWS
Technology
Automating Client Follow-Up with an AI Calling Agent
An AWS-native AI voice agent that runs post-project client check-ins, flags escalation risk, and auto-generates follow-up reports.
Technology
Accelerating Knowledge Access with a Generative AI Assistant
A secure, serverless generative AI assistant on AWS giving distributed innovation teams instant access to program knowledge.
Technology
Modernizing Inmate Communications with Secure Cloud AI
Rebuilding a correctional communications platform on AWS to improve call quality, automate compliance, and secure access.
HEALTHCARE
Building a Clinical-Grade AI Platform for GLP-1 Weight Care
Designing and building a HIPAA-aligned platform that pairs a patient app and clinician portal with a dual-pipeline clinical AI.
AWS AI Competency FAQs
Why work with an AWS AI Competency Partner?
AWS AI competency partners possess deep platform expertise along with comprehensive generative and agentic AI capabilities, making them a strong fit for leading AI projects in AWS environments. This is a validated competency, not self-proclaimed, so you can be confident that these partners have the expertise and experience deemed necessary by AWS for executing generative and agentic AI projects in AWS environments.
Is it the same as an AWS certification?
No. AWS certifications are awarded to individuals. AWS AI Competency is a partnership badge awarded to an organization that AWS has evaluated for both AI capabilities and deep AWS knowledge.
How rigorous is the validation?
The AWS AI Competency validation is extremely rigorous and requires partners to pass strict technical reviews and offer proof of production-grade deployments, showcasing their hands-on experience. The partners must also prove alignment to AWS’s Well-Architected Framework.
Does the AWS AI Competency cover both generative and agentic AI?
Yes. It was previously focused on just generative AI and named AWS Generative AI Competency, but in late 2025, agentic AI was added as another category within this competency, and it was retitled to AWS AI Competency. It can now be earned in both generative and agentic AI categories.