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We're excited to announce that I'll be representing Stacksync at Data Council 2025 in Oakland, California from April 22-24, a premier technical event where data truly meets intelligence. As co-founder of Stacksync, I'm looking forward to connecting with AI engineers, CTOs, Heads of Data, and fellow innovators who are building the future of data.
In today's AI-driven landscape, real-time data synchronization has become more critical than ever. Every AI breakthrough starts with data—specifically, consistent, reliable, and instantly available data across systems. This aligns perfectly with our mission at Stacksync, where we've built a platform that enables true bi-directional, real-time synchronization between your critical operational systems.
Data Council brings together over 1,000 technical attendees and features 100+ deep-dive talks from industry leaders. This event offers a unique opportunity to:
As AI capabilities expand, the need for seamless data synchronization becomes increasingly apparent. Many organizations are struggling with fragmented data across CRMs, databases, ERPs, and other operational systems. This fragmentation creates significant barriers to effective AI implementation:
At Stacksync, we've seen firsthand how these challenges can impede AI initiatives. Our platform addresses these issues by providing sub-second synchronization between your critical systems, ensuring your AI tools always have access to the most current, consistent data available.
Data Council 2025 features an impressive lineup of sessions across multiple tracks. We're particularly interested in:
These sessions will explore the backbone of modern data systems—exactly where Stacksync operates to ensure data flows seamlessly.
Understanding how organizations are operationalizing machine learning will help us better support customers integrating our synchronization capabilities into their ML workflows.
As foundation models become increasingly important, the need for real-time, accurate data feeding these systems grows exponentially.
These practical sessions will showcase how real-world AI applications are being built and deployed, often highlighting integration challenges we're uniquely positioned to solve.
If you're attending Data Council 2025, I'd love to meet with you to discuss:
I'll be available throughout the event for one-on-one meetings. Whether you're looking to solve specific data integration problems or just want to chat about the future of data synchronization in AI workflows, I'm here to help.
You might wonder why a data synchronization platform like Stacksync is so relevant at an AI-focused event. The answer is simple: effective AI requires consistent, reliable data.
When your AI applications need to:
The underlying data synchronization infrastructure becomes critical. That's where Stacksync's real-time, bi-directional capabilities make all the difference.
I have limited availability during the event, so I recommend scheduling a meeting in advance. This way, we can ensure we have dedicated time to discuss your specific data integration needs and how Stacksync might help.
To schedule a meeting: Send an email to ruben@stacksync.com with "Data Council Meeting" in the subject line, and I'll get back to you promptly to arrange a time that works for both of us.
Data Council 2025 promises to be an exceptional event with outstanding speakers, valuable networking opportunities, and cutting-edge insights. I'm looking forward to being part of the conversation and connecting with fellow data enthusiasts.
If you haven't registered yet, tickets are still available. The event will be held at the Oakland Scottish Rite Center (also known as "The Temple of Data" for this event) from April 22-24, 2025.
Whether you're already using Stacksync or just beginning to explore solutions for your data integration challenges, I hope to see you there!
About Stacksync: Stacksync delivers reliable, real-time, truly bi-directional data synchronization purpose-built for operational systems, eliminating integration complexity and ensuring trusted data consistency without the overhead of traditional iPaaS or the limitations of point solutions.
