AWS Partnership

Build and operate enterprise AI on AWS

Why We Build on AWS

Enterprise AI needs more than a model. It needs secure data access, dependable infrastructure, monitoring, identity, and a clear operating model. We use AWS services to bring those pieces together and build systems that fit the way your organization works.

AWS-Native Depth

AWS services selected for the workload

As an AWS Advanced Tier Services Partner with a Strategic Collaboration Agreement, we work across the AWS AI, data, security, and modernization stack.

AWS Advanced Tier Partner

Strategic Collaboration Agreement

What the partnership changes

Our AWS relationship helps us connect solution design, delivery planning, and current AWS guidance in one customer engagement. We start with your workload, security needs, and operating goals, then identify the architecture and AWS programs that fit.

Architecture review for your production workload

Agentic AI patterns built on Bedrock, AgentCore, Quick Suite, and AWS Transform

Security and governance designed around your requirements

What we build on AWS

Services matched to your workload.

Start with a focused assessment, pilot, implementation, or managed service. We define the target workflow and success measures with your team, then select the AWS services and delivery plan that fit.

AI, Data & Developer Experience

SageMaker Unified Studio, SageMaker Lakehouse, vector search, semantic layers, Bedrock, AgentCore, and spec-driven delivery.

Agentic CloudOps & Resilience

CloudWatch observability, automated investigation, resilience testing, ARC failover, Resilience Hub, and AI FinOps.

Applied AI Business Apps

Amazon Quick Suite, Amazon Connect, AI agents, omnichannel service, secure WorkSpaces, intelligent messaging, and workflow automation.

Migrations & Modernization

AWS Transform, VMware migration, Windows and .NET modernization, mainframe transformation, and AI-ready cloud foundations.

Security, Identity & Governance

Data perimeters, delegated access, policy validation, secrets lifecycle, detection and response, and AI runtime governance.

AWS Coordination

Coordinate architecture guidance, AWS program inputs, procurement paths, delivery responsibilities, and implementation planning with your AWS team.

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Amazon Bedrock AgentCore

Use managed AWS capabilities for agent runtime, session isolation, credentials, identity-aware authorization, memory, and evaluation.

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Amazon Bedrock

Foundation model access, knowledge bases, prompt flows, multi-agent orchestration, tool use, and Bedrock Guardrails for production AI systems.

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Strands Agents & MCP

Build modular agent applications with the open-source Strands Agents framework and supported Model Context Protocol connections.

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AgentCore Evaluations & Memory

Store selected session context and evaluate agent traces against the quality and operating measures your team defines.

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Amazon Connect + Nova 2 Sonic

Design voice-assisted contact-center workflows using Amazon Connect and Nova 2 Sonic through Amazon Bedrock.

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Amazon SageMaker Unified Studio

Unified data, analytics, AI, ML, lakehouse, catalog, and governed collaboration for production AI programs.

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Amazon Quick Suite

Agentic workspace for business users: enterprise search, research, BI, automation, workflows, and governed actions from one workspace.

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Bedrock Knowledge Bases + S3 Vectors

Modern RAG and semantic retrieval patterns using S3 Vectors, OpenSearch Serverless, and managed Bedrock retrieval for grounded agents.

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AWS Transform

Assess and modernize supported VMware, Windows, .NET, mainframe, and custom workloads with current AWS Transform capabilities.

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AWS Security & Governance

Use IAM Identity Center, CloudTrail, Bedrock Guardrails, AgentCore identity controls, and runtime records to support your governance program.

Agentic Runtime at Scale

Agentic systems require persistent execution, state management, and controlled interaction with enterprise data and services. AWS provides the primitives required to support these behaviors reliably across environments.

Control, Observability, and Governance

For long-running AI workflows, define access, monitoring, logging, review, and stop controls around the actions and data in scope. We select and test the AWS services that support those requirements.

From Design to Production

We use practical AWS patterns as a starting point, then test the design against your workload, security needs, integrations, and operating plan before deployment.