Session
Google Cloud Next '25 - Appsheet: Accelerate AI adoption into the flow of work
At Google Cloud Next '25, this featured breakout session (BRK1-084) showcased how organizations can move past basic AI chat screens and inject actionable GenAI directly into daily business operations. In this high-impact customer panel segment, Senior Software Architect Camron Lupton joins Seegrid’s Director of IT and Google Cloud's Appsheet Product Manager to explore the real-world architecture, deployment strategies, and massive automation potential of AppSheet’s native AI capabilities across organizations of all sizes.
How do you transition an organization from passive AI tools to intelligent, agentic workflows that actually execute business operations?
In the featured panel half of this Google Cloud Next '25 breakout track, Camron Lupton (Senior Software Architect at QREW Technologies) bridges the gap between raw cutting-edge technology and practical, scalable execution. Engaging in an interactive, rapid-fire strategy exchange with Matthew Zito (Appsheet Product Manager, Google Cloud) and Clayton Mathis (Director of IT, Seegrid), this session unpacks how low-code architectures are revolutionizing modern workplaces.
While Seegrid shares their frontline enterprise automated material handling use cases, Camron draws on QREW’s massive cross-industry footprint to map out the future of intelligent app building.
Key takeaways from this panel segment include:
Demystifying AI Tasks in AppSheet: Tactical blueprints for leveraging native GenAI features—including structured data extraction, automatic text categorization, dynamic row generation, and smart summarization—to completely replace manual data entry.
Practical frameworks for how QREW Technologies implements governed, high-performance low-code ecosystems across businesses ranging from agile small operations to sprawling enterprise architectures.
Future-Proofing Automations: A look at how forward-thinking development teams can build predictive, automated loops that safely route unstructured operational data into complex enterprise relational systems.
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