Centific is proud to introduce our GenAI Foundational Workshop, designed to help re-tail and eCommerce organizations implement GenAI solutions that drive tangible value on the AWS platform. This Workshop empowers your AI teams to scale beyond the proof-of-concept stage, moving into real-world production on AWS, where they can ad-dress key challenges like fluctuating customer demands, operational scalability, and per-sonalization at scale.

Our experts guide you through the essential aspects of an AI data foundry platform on AWS, showcasing how it integrates multi-turn conversational AI for eCommerce shop-ping assistants. This integration enables your brand to offer personalized product rec-ommendations, streamline purchasing, and provide real-time customer support with AWS services. Furthermore, the data foundry curates and labels complex datasets on AWS, allowing for precise demand forecasting and real-time tracking of trading partner relationships, improving both customer experiences and supply chain agility.

Workshop structure

The GenAI Workshop consists of a series of joint architecture design meetings, ranging from 1 to 2 hours per session (up to 8 hours total), focused on the following domains:

• Data Modernization: Prepare your data platforms for AI scalability, ensuring that eCommerce-specific data, from purchase history to browsing patterns, is accessible and actionable for personalization and customer segmentation.

• Data Supply: Build effective data pipelines to manage omnichannel sales data, user behavior insights, and product interaction patterns, empowering your AI models to make informed recommendations and streamline supply chain management.

Model Fine-Tuning: Customize AI models to address retail-specific challenges, like increasing conversion rates through predictive recommendations, reducing cart abandonment, and forecasting demand with precision.

• Infrastructure & Deployment: Discover best practices for deploying GenAI in cloud environments, ensuring high performance, reliability, and scalability to meet the demands of high-traffic shopping seasons and peaks.

• GenAI Agents & Chatbots: Explore AI-powered agents that can engage customers in multi-turn conversations, providing tailored product recommendations, answering inquiries in real-time, and supporting customer service needs throughout the purchasing journey.

Each session emphasizes discovery, design, and education, showing how an AI data foundry platform streamlines the AI lifecycle and enhances flexibility, scalability, and security within the retail context.

Deliverables

• Technical Deep-Dive Discovery Sessions: These collaborative workshops with Centific’s AI experts are designed to align your GenAI strategy with specific retail and eCommerce goals, such as loyalty program integration, dynamic pricing, and personalized marketing.

• Future-State Architecture Diagram: A detailed diagram outlining the GenAI framework tailored to your platform’s needs, supporting everything from real-time personalization to efficient checkout and post-purchase support.

• Recommendations Report: This summary provides key insights and strategic choices, helping you prioritize AI use cases like personalized product recommendations, demand forecasting, and supply chain optimization to maximize impact.

• Cost Estimation: With Centific’s cost estimation tools, you’ll gain a forecast of the Total Cost of Ownership (TCO) for your GenAI deployment, ensuring that your investment aligns with financial goals and scales as needed.

• Implementation Proposal: This detailed plan outlines the scope of Centific’s services to bring your retail-focused AI solutions into production, complete with action steps and a timeline to get started.

Timeline

The workshop is structured to be completed in approximately two weeks, depending on the availability of your project sponsor and technical teams. We also offer the option of conducting the Workshop as an 8-hour onsite, in-person session.

Next Steps

Typical next steps include proof-of-concept deployments to demonstrate the capabilities of your future-state AI design, followed by full production implementation. These steps ensure a smooth transition from concept to production and provide a framework to explore AI and machine learning capabilities tailored to your organization’s retail-specific needs.