AI Platform & Application Architecture Assessment
Data & AI
Motivation
Unlock the full potential of your business with our comprehensive AI and application architecture assessment, designed to ensure your organization is fully prepared to host scalable AI workloads in the cloud. Our service evaluates your AI maturity ensuring that you possess a robust AI operating model that aligns with your business goals. We also assess your cloud and AI infrastructure, ensuring it is scalable, secure, and capable of handling complex AI tasks. Additionally, our assessment covers backend integration and application architecture, ensuring they meet both functional and non-functional requirements for seamless AI deployment. By identifying gaps and providing actionable insights, we help you confidently transition to cloud-based AI, driving innovation and efficiency within your enterprise.
What we bring
With over 20 years of experience in software and data architectures for many of the world’s largest enterprises, PRODYNA is well-equipped to help you identify potential risks and gaps in your AI platform and application architecture.
Our expertise in this area includes:
- Cloud Expertise: As a member of the Cloud Native Computing Foundation, we specialize in designing robust cloud infrastructure.
- Software Architecture: Our extensive experience in software architecture has been developed through designing and developing hundreds of custom software solutions.
- Operations Model: We possess strong proficiency in operating software applications, with a particular emphasis on artificial intelligence.
- Cross-functional Know-how: With years of experience working with Azure cloud and developing custom software, we provide comprehensive services ranging from initial development to ongoing operation and maintenance of applications.
What you need
To successfully perform the AI Platform and Application Assessment, your organization will need to provide:
- AI Use Case Requirements: Clearly defined functional and non-functional requirements that the AI application must meet.
- Preliminary Architecture: A solid draft of the target architecture to serve as the basis for the architecture check.
- AI Governance Framework: A foundational governance framework to ensure security, monitoring, and responsible AI practices are standardized.
- Operations Model: A detailed description of the current operations model for AI applications, including MLOps and FinOps.
- Data Pools: A extensive understanding of the required data pools.
- Business Application Teams: Access to teams who can provide information on integrating the AI application into existing business applications and workflows, if applicable.
What you get
We will tailor the assessment to your organization's specific needs to minimize time and cost. PRODYNA will guide you and your employees through the following phases:
Application Foundation
(1-2 days)
Infrastructure: Verify that your (cloud) infrastructure can deliver the required performance for your AI application while staying within cost constraints.
Data Connectivity: Ensure that your application can securely access the necessary data for tasks such as RAG, data augmentation, or data extraction.
Development: Verify that the developer experience is optimized to enable efficient development, incorporating best practices for MLOps.
Compliance: Confirm that your AI governance framework can be applied effectively to ensure a safe and reliant usage of your AI application.
Responsible AI: Identify the impacts of the AI application on your business and ensure they are managed according to government guidelines.
Monitoring: Ensure your current monitoring capabilities are sufficient to detect security issues and collect relevant KPIs, such as user feedback, to measure application success.
Application Specifics
(1-3 days)
Requirements Engineering: Identify any missing or overlapping requirements to ensure all aspects of the use case are covered comprehensively.
Software Architecture: Evaluate the current architecture against the requirements and basic conditions to ensure it is suitable for the project.
Cloud Services: Verify that the suggested cloud services meet compliance and performance requirements, such as respecting EU data boundaries.
Security: Determine the best way to enable access control on all layers of the application, ensuring users do not access data they are not authorized to.
Integration: Ensure that the business application can seamlessly integrate the AI application, allowing for smooth incorporation of AI capabilities into the business workflow.
API Documentation: Present API contracts to software development teams, ensuring they have a clear understanding of the interfaces and can develop accordingly.
Quick facts
- Duration: 3-5 days depending on the scope.
- Assesses whether your current AI readyness.
- Reduces risk before proceeding to full scale application development.
Benefits
- Well-Architected: Our AI Governance Framework ensures scalable, reliable, and cost-efficient AI solutions.
- Early Design Changes: Identify and address architectural gaps early to avoid costly rework.
- Detailed Roadmap: Clear steps help your team resolve open issues efficiently.
- Compliance: Aligns with regulations like the EU AI Act for greater security and assurance.
Contact us
for more information.
David Wainwright
