Join Data Reply, DoIT, and AWS for an insightful event on transitioning Generative AI projects from PoC to production.
Register now to gain actionable insights on transitioning from PoC to production in Generative AI and explore the capabilities of AWS services.
Join Data Reply, DoIT, and AWS for an insightful event on transitioning Generative AI projects from PoC to production. Learn about the transformative potential of Generative AI, explore AWS’s powerful tools and services, and gain actionable insights to overcome challenges in scaling AI solutions.
09:30 AM
09:45 AM
1) Welcome and Opening Remarks
Speaker: Reply (Hédi Aloui)
Duration:15 mins (09:30–09:45)
Overview: Introduction to the event and partners
10:15 AM
10:45 AM
3) Driving Organizational Adoption and Change Management
Speaker: Sascha Heyer
Duration: 30 mins (10:15–10:45)
Overview: Facilitating readiness and aligning teams for AI implementation success.
10:45 AM
11:00 AM
Coffee Break
11:00 AM
11:30 AM
4) AWS Perspective: Tools and Services for Generative AI
Speaker: Kabil Jaballah
Duration: 30 mins (11:00–11:30)
Overview: Overview of AWS services like Bedrock and SageMaker for scalable AI solutions.
11:30 AM
12:00 PM
5) Panel Discussion:Lessons Learned in PoC to Production (Reply x DoIT x AWS)
Panelists: Reply Representatives from Data Reply, DoIT and AWS
Duration : 30 mins (11:30–12:00)
Overview: Real-life insights, expert guidance, and audience Q&A on transitioning AI projects.
This event offers a unique opportunity to gain practical knowledge, interact with experts from Data Reply, DoIT, and AWS, and prepare your organisation for the next step in Generative AI adoption.
Business Leaders and Decision Makers
Product Managers
CTOs and Technology Leaders
Data Reply
Data Reply est la société du groupe Reply offrant une large gamme de services d'analyse avancée et de données alimentées par l'IA. Nous opérons dans différentes industries et fonctions commerciales, en travaillant directement avec des professionnels de niveau exécutif et des directeurs généraux leur permettant d'obtenir des résultats significatifs grâce à l'utilisation efficace des données.