Dedalus – GenAI Accelerator with Amazon Bedrock

Organizations are moving beyond isolated AI experiments. The challenge is no longer only selecting a foundation model or building a demonstration. It is connecting a relevant business use case to trusted data, security controls, responsible AI practices, scalable architecture, operational processes and measurable outcomes.

Dedalus - AI Accelerator with Amazon Bedrock is a modular professional services engagement designed to turn a prioritized AI opportunity into a secure, governed and production-ready capability on AWS. The service supports generative AI applications, retrieval-augmented generation (RAG), intelligent document processing, enterprise assistants and agentic workflows, according to the customer’s business need and technical maturity.

The engagement is built around the Dedalus AI Foundation approach. Rather than treating the use case as an isolated application, Dedalus addresses the enabling foundation across five dimensions: Data, Governance, Platform, Engineering Excellence and FinOps. This creates the conditions to scale the first solution and reuse architecture, controls, delivery practices and operational knowledge for subsequent initiatives.

Amazon Bedrock provides managed access to foundation models and capabilities for building generative AI applications. Dedalus adds the specialist services required to evaluate the use case, select an appropriate model and architecture, integrate enterprise data and systems, implement controls, engineer the solution, prepare operations and enable the customer team.

The final scope is tailored to the customer through an AWS Marketplace private offer. Depending on maturity and objectives, the engagement can start with opportunity framing and foundation assessment, accelerate an existing prototype toward production, or modernize an existing AI workload for Amazon Bedrock.

• Organizations with a validated AI opportunity that need a reliable path to production;
• Teams with an existing prototype or proof of concept that lacks governance, security, integration, observability or operating readiness;
• Organizations that want to adopt Amazon Bedrock while retaining flexibility in model selection and avoiding unnecessary infrastructure management;
• Business units seeking an AI solution connected to enterprise data and workflows, with technology, security and governance stakeholders involved from the beginning;
• Customers modernizing an existing generative AI workload or consolidating AI capabilities on AWS.

• Enterprise knowledge assistants and RAG-enabled search;
• Customer and employee service automation;
• Intelligent document processing and contextual extraction;
• Content summarization and generation with enterprise controls;
• Decision support based on governed business information;
• Agentic workflows that invoke approved APIs and systems;
• Modernization or migration of existing generative AI workloads to Amazon Bedrock.