Kyndryl is an AWS Premier Tier Services Partner, and together we focus on helping businesses progress with our industry focused solutions.

Kyndryl signed a multi-year Strategic Collaboration Agreement with AWS to accelerate client adoption of Generative AI solutions. This includes the creation of the Kyndryl and AWS Innovation Factory, which aims to co-create Generative AI and ML solutions tailored for industry use cases including - Consumer Product Goods (CPG), Retail, Quick Serve Restaurants (QSR), Grocery and B2B distribution space.

As part of this assessment, Kyndryl Consult will help organizations provide strategic and delivery approach, technology stack assessment and future state recommendations. Kyndryl’s Generative AI assessment includes - comprehensive evaluation of current state, Target operating model (TOM), High level reference Architecture and building transformational roadmap for quick wins.

Key Retail and Consumer Goods use cases include:

• Conversational Commerce, marketing and hyper personalization
• Optimizing Supply chains, Order management, Inventory and Transportation management
• Smart Warehouse and Operational analytics (AIOps/MLOps)
• Retail Planograms and Revenue Growth management
• Consumer and Employee experience

To enable GenAI capabilities start by setting up the right data foundation platform, ensure data quality, security and governance. We recommend -

• Initial assessment to identify and evaluate all source data
• Build data foundation platform and ensure data quality across business entities
• Analyze data sources for compatibility with AI/ML tools and platforms
• Fix master data issues and recommend data cleansing
• Review best-in-class technology solutions available that organizations can incorporate leveraging AWS technologies- Bedrock, Amazon Q, QuickSight, SageMaker and others.

Roadmap and Recommendations -

• Recommendations for suitable data platforms, AI solutions, frameworks, and tools for identified use cases
• Documentation of recommended solutions capabilities, risks, and limitations.
• Identification of areas where data, analytics and AI can drive business growth, efficiency, and innovation
• High level reference architecture leveraging existing tech investment
• Development of an implementation roadmap with high-level timelines, resources, and dependencies
• Report out with priority use cases, recommendations, findings, highlighting benefits and challenges of recommended solutions
• Proof-Of-Concept (POC) proposal for applicable/ prioritized use cases