Zühlke GenAI Product Delivery on Amazon Bedrock

Zühlke offers professional services to deliver a GenAI MVP leveraging Amazon Bedrock using the Zühlke Augmented Generation (ZAG) framework. ZAG is a pre-built platform to deliver performant, secure, and scalable GenAI bespoke products.

This offering is designed to rapidly move from ideation to a production-ready GenAI solution, utilizing a structured approach comprising Strategy & Vision, Discovery, Proof of Concept (PoC) delivery, and MVP execution. Organizations will gain access to industry expertise, robust methodologies, and a scalable GenAI solution that seamlessly integrates into existing systems.

• Applicable across industries such as Insurance, Banking, Manufacturing, Healthcare, Life Sciences, and Government
• Ideal for organizations aiming to explore high-impact GenAI applications with clearly-defined performance targets, without compromising governance and compliance
• Addresses common challenges such as scalability, risk mitigation, quick time-to-market, and integration with existing processes

• Accelerated Time-to-Value: The structured five-step approach ensures a swift transition from concept to a production-ready MVP, minimizing the developmental timeline.
• Tangible Business Impact: By focusing on high-value use cases, the solution enhances operational efficiencies and drives measurable business outcomes.
• Cost Efficiency: Harnessing pre-built accelerators reduces both development and operational costs.
• Reduced Risk and Compliance: Zühlke's deep expertise ensures adherence to regulations such as GDPR and the EU AI Act, reducing legal and ethical risks associated with GenAI deployments.
• Secure and Scalable Solutions: Robust architectures validated by AWS ensure the solutions are resilient, scalable, and securely integrated into existing business processes.

• Proven expertise as an AWS Advanced Partner
• Extensive experience with deploying GenAI in regulated environments
• Proven framework for responsible AI development. Partnership with TÜV Süd

• Defining GenAI Vision: Workshops to establish a clear vision for GenAI integration, outlining strategic objectives and desired improvements.
• Identifying High-Impact Use Cases: Selection of use cases with the potential to yield significant results in terms of efficiency and innovation.
• Implementation Roadmap: Development of a comprehensive roadmap for MVP deployment with strategies for seamless integration.
• Responsible AI Governance: Establishing frameworks to maintain ethically compliant AI practices throughout the lifecycle of the solution.

• Strategy & Vision: Conduct workshops to define GenAI vision and assess AI readiness, ensuring alignment with organizational goals.
• Discovery: Propose solution concepts by comprehensively understanding user needs, validating feasibility through targeted research and describing the business case.
• Proof of Concept (PoC): Demonstrate technical feasibility in a controlled environment, collecting substantial user feedback to inform MVP development. Assess the business case's viability.
• Minimum Viable Product (MVP): Develop the successful PoC into a robust, production-ready product, integrating seamlessly within the client's operations.
• Integration & Governance: Utilize AWS services to ensure scalability, maintainability, and security, alongside stringent governance measures for responsible use.

• PoC and production-ready MVP: Receive fully operational prototypes that demonstrate concept feasibility and readiness for integration.
• Validated GenAI Strategy and Roadmap: Documentation detailing long-term strategies for GenAI deployment across business functions.
• Comprehensive Documentation: Access presentations, roadmaps, and detailed implementation guides that facilitate seamless execution and adoption.
• Scalable Solution Framework: A ready-to-use solution equipped with a backlog for future enhancements and use case expansion.
• Ongoing Optimization: Continuous improvements through governance and feedback mechanisms to maximize output and efficiency.

• Amazon Bedrock for AI model deployment
• Amazon S3 for data storage
• Amazon Textract for document ingest and parsing
• Amazon OpenSearch Service for document indexing and searchability
• Amazon ECS for hosting the GenAI solution
• Amazon DynamoDB for conversation history and feedback storage