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Join us on February 18th and discover how to implement AI-driven solutions in your business.

See a live demo of Pluto7's Planning in a Box and Pi Agent in action.
 

Key Takeaways:

1) How Pluto7's Planning in a Box uses GenAI and multi-agent systems to revolutionize demand sensing and forecasting.
2) The value of Pi Agent in automating tasks, improving decision-making, and enhancing forecasting precision.
3) The role of Google Cloud’s advanced infrastructure in creating a robust AI foundation.
4) Real-world case studies showcasing measurable outcomes and efficiency gains.
Speakers
Minh Giang

SAP Solutions Engineer
Google
Manju Devadas

Founder & CEO
Pluto7
Tarun Kumar

VP of Sales
Pluto7
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Agenda
10:00 - 10:05 AM | Meet and Greet

Introduction and event goals.

10:05 - 10:20 AM | AI in Demand Sensing and Forecasting

Explore how AI-powered demand sensing is reshaping supply chains. Learn about integrating POS data, customer insights, and market trends to achieve higher accuracy, with the support of AI Agents.

10:20 - 10:30 AM | Unlocking Potential with Google Cortex and AI Agents

Discover how Google Cloud’s advanced infrastructure, including the Google Cortex Framework, provides the robust data foundation necessary for solutions like Planning in a Box. Learn how this technology accelerates AI adoption and enables multi-agent systems to work effectively across the supply chain.

10:30 - 10:40 AM | Case Studies: AI-Driven Forecasting in Action

Hear real-world examples of how businesses are reducing forecast errors, increasing demand visibility, and driving operational efficiency with Pluto7's AI-powered solutions, supported by AI Agents.

10:40 - 10:50 AM | Live Demo: Planning in a Box and Pi Agent

See a hands-on demonstration of Planning in a Box in action, showcasing its multi-agent capabilities and practical applications. Engage in an interactive Q&A session with our AI experts, including insights from Pi Agent and other AI Agents.

10:50 - 11:00 AM | Q&A and Closing Notes

Final thoughts, addressing audience queries, and next steps for implementing AI-driven demand forecasting.

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