Quantiphi Joins AWS in Atlanta to Discuss Apache Iceberg, Agentic AI, and the Future of Intelligent Lakehouses

As enterprises accelerate AI adoption, the data foundation beneath every initiative is becoming more important than ever. Organizations are no longer asking whether they need scalable analytics platforms. They are asking whether their data architecture is open, interoperable, governed, real-time, cost-efficient, and ready to support the next generation of agentic AI workloads.

Quantiphi recently joined AWS in Atlanta for “The Apache Iceberg on AWS Advantage: Building Powerful Lakehouses for the Agentic AI Era,” a customer-focused event exploring how open data architectures, Apache Iceberg, and AWS services are shaping the future of enterprise analytics and AI. The event brought together domain experts, data and analytics leaders, architects, BI teams, engineers, and decision-makers from multiple industries to discuss a fast-moving shift in enterprise technology.

Why Data Architecture Is Now a Strategic Priority

Across industries, enterprises are moving beyond traditional data modernization. The focus is shifting toward building AI-ready, intelligent data platforms that can support not just analytics, but decision-making at scale.

This shift is being driven by a new class of workloads—agentic AI systems that don’t just generate insights, but actively reason, retrieve, and take action.

To support this, data platforms must evolve from static repositories into dynamic, governed, and context-rich ecosystems.

Apache Iceberg and the Rise of Open Lakehouse Architectures

Apache Iceberg is becoming a critical open table format for business-critical analytics and AI/ML workloads because it helps organizations modernize data platforms without locking data into a single engine, tool, or vendor ecosystem.

A key theme throughout the event was that agentic AI requires more than powerful models. To reason, retrieve, analyze, and act effectively, AI agents need governed access to trusted, contextual enterprise data with strong interoperability and performance. Apache Iceberg helps address these requirements by creating an open, scalable table foundation that can work across analytics engines, data platforms, and AI workflows. This interoperability is one of the biggest drivers of Iceberg adoption.

Why Agentic AI Demands a New Data Foundation

Enterprises want the freedom to use the right compute engine for the right workload while maintaining a consistent data foundation. With Iceberg on AWS, organizations can reduce data duplication, improve cross-platform access, simplify migration strategies, and create a more flexible architecture for both analytics and AI.

At the same time, many enterprises struggle to move from Iceberg interest to production adoption. Common challenges include unclear migration priorities, catalog and governance design, table maintenance strategy, performance tuning, workload interoperability, and the operational complexity of moving production data pipelines to open table formats. Without a clear adoption framework, organizations risk creating another fragmented data layer instead of a trusted foundation for analytics and AI.

How Quantiphi Is Accelerating Lakehouse Modernization

At the event, Quantiphi showcased how we help enterprises move from fragmented legacy systems to AI-ready lakehouse architectures using QDAP and Qatapult. Representing Quantiphi, Lisa Waters, AWS Alliance Lead, and Prudhvi Atluri, Senior Solutions Specialist, shared how Quantiphi helps customers modernize their data estates using QDAP and Qatapult. Their session highlighted how enterprises can move from fragmented legacy platforms to AI-ready lakehouse architectures that support analytics, machine learning, real-time insights, and agentic AI use cases at scale.

QDAP helps organizations ramp up Apache Iceberg adoption by turning lakehouse modernization into a repeatable path. By combining open architectures like Apache Iceberg, Amazon S3 Tables, AWS-native data services, and strong governance patterns, we help customers build an intelligent data foundation that gives agentic AI systems the trusted enterprise context they need to reason, act, and deliver business value at scale.

Through QDAP, Quantiphi helps customers accelerate Iceberg adoption by assessing the current data estate, identifying high-value modernization workloads, designing governed Iceberg table architectures, and enabling migration patterns that reduce complexity. With AWS capabilities such as Amazon S3 Tables, organizations can store and manage Apache Iceberg tables in Amazon S3 while integrating with services such as AWS Glue Data Catalog and AWS analytics services. This helps customers move from pilot implementations to governed, production-scale Iceberg adoption across enterprise workloads.

The event agenda covered the full modernization journey, including AWS’s vision for Apache Iceberg, recent Iceberg innovations, Iceberg’s role in AI foundations, interoperability, real-time analytics, fully managed lakehouse architecture, migration strategies, and a hands-on workshop for building with Apache Iceberg.

The Future of Lakehouses: From Data Platforms to AI Foundations

For enterprises, the message was clear: the future lakehouse is not only a data platform. It is becoming the operating foundation for AI-driven decision-making.

As agentic AI continues to reshape how businesses turn data into action, open and intelligent lakehouse architectures will play a central role in enterprise transformation. Quantiphi is proud to collaborate with AWS and customers across industries to help accelerate Apache Iceberg adoption, modernize enterprise data foundations, and build the next generation of AI-ready lakehouses.

Ready to Build Your AI-Ready Lakehouse?

Move beyond fragmented data platforms and unlock the full potential of agentic AI.

Connect with Quantiphi to design, modernize, and scale your data foundation for the next generation of enterprise intelligence.