GenAI Discovery & Assessment – Identify, Validate, Plan Your AWS Journey

Generative AI offers possibilities for businesses, depending on the identification of suitable use cases. Atlasticity’s AWS-focused GenAI Discovery Process helps organizations move from concept to implementation by pinpointing valuable opportunities and developing a proof of concept (POC) within a secure, controlled environment.

Key Capabilities:

● High-Impact Use Cases: Workshops designed to identify and prioritize GenAI opportunities.

● Feasibility & ROI Analysis: Provides guidance regarding custom AWS solutions versus off-the-shelf alternatives.

● Implementation Plan: Outlines a phased roadmap with architecture and resourcing plans aligned to AWS.

● POC Demonstration: Includes a demo created by Atlasticity using synthetic or non-sensitive data, without production system access.

What It Solves

● Lack of Generative AI Strategy or Direction - Helps organizations unclear on where or how to begin their AI journey.

● Underutilized Data Assets - Surfaces opportunities to leverage existing data for predictive insights and automation.

● Disconnected Business and Tech Objectives - Aligns AI initiatives with core business priorities to ensure relevance and ROI.

● Tool Overload or Misalignment - Simplifies the AWS AI/ML ecosystem, ensuring the right services are used for the right purposes.

● Risk of Failed AI Projects - Reduces implementation risk by validating readiness and aligning on feasible, high-value use cases.

Service Outcomes

● Potential Use Cases: Identify and prioritize GenAI opportunities by conducting workshops.

● Feasibility & ROI Analysis: Guidance on choosing between custom AWS solutions or off-the-shelf options.

● Implementation Plan: Step-by-step roadmap with AWS-based architecture and resource allocation.

● POC Demonstration: Demo using synthetic or non-sensitive data in an Atlasticity environment; production access not needed.

FAQs

1. What is GenAI Discovery & Assessment? A GenAI Discovery & Assessment on AWS is a structured evaluation that helps organizations identify AI opportunities, assess their current capabilities, and plan how to leverage AWS AI/ML services to meet business goals.

2. Why should we conduct a GenAI Discovery & Assessment? It ensures alignment between AI initiatives and business objectives, identifies quick wins, highlights gaps in data and skills, and creates a clear roadmap for AI adoption on AWS.

3. What AWS services are typically evaluated during a GenAI Discovery & Assessment?

Common services include:

● SageMaker: A fully managed service that helps you build, train, and deploy machine learning models at scale.

● Bedrock: A platform for building and scaling generative AI applications using foundation models.

● OpenSearch: A search and analytics suite that enables fast search, data exploration, and real-time insights.

● Amazon Q: An AI-powered assistant designed to answer business questions, generate content, and automate tasks.

4. How long does a GenAI Discovery & Assessment usually take? The timeline varies but typically ranges from 6 to 8 weeks depending on organizational complexity and scope.

5. Do we need a lot of existing AI expertise to start? No, the assessment helps identify skill gaps and provides guidance on roles, tools, and training needed for successful AI adoption.

6. How is data privacy handled during the assessment? Data governance and compliance requirements are reviewed upfront to ensure all AI initiatives meet relevant regulatory and organizational policies.

7. What happens after the GenAI Discovery & Assessment? Typically, organizations quickly move into the implementation phase by scaling successful AI POC solutions into production.

8. How does Atlasticity support ongoing GenAI model management? Atlasticity provides Cloud Operations Services for continuous AWS infrastructure optimization, monitoring, technical remediation, and governance of AI models.