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AI agents are starting to change how data engineering teams operate. But for data leaders, the bigger question is: 𝐇𝐨𝐰 𝐝𝐨 𝐰𝐞 𝐦𝐚𝐤𝐞 𝐭𝐡𝐞𝐦 𝐫𝐞𝐥𝐢𝐚𝐛𝐥𝐞, 𝐬𝐜𝐚𝐥𝐚𝐛𝐥𝐞, 𝐚𝐧𝐝 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧-𝐫𝐞𝐚𝐝𝐲? From investigating pipeline failures and tracing dependencies to automating root cause analysis and generating fixes. ⏱️ But moving beyond experimentation brings its own challenges. We at Upriver, are hosting a virtual roundtable for Data Leaders: 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬 𝐟𝐨𝐫 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬: 𝐁𝐞𝐬𝐭 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞𝐬 & 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬 👾 Sumit Gupta 📊 from Superhuman and Omri Lifshitz from Upriver will be sharing their perspectives on AI adoption in data engineering, and the challenges of bringing agents into production data systems. 📅 𝐃𝐚𝐭𝐞 & 𝐓𝐢𝐦𝐞: October 27, 2026 | 9:30 AM PT 👉 𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐡𝐞𝐫𝐞: https://lnkd.in/e8kHVHCK This won't be a product demo or a presentation-heavy webinar. It's an open discussion for data leaders to exchange perspectives, share challenges, and explore what AI-driven dataOps could look like in practice. #DataOps #GenAI #MLOps #AIOps #DataEngineering #ETL #AI #AIAgents #LLMOps #AIWorkflows LLMOps Space

Your team adopted AI. The backlog kept growing. The time goes to tracing incidents across tools, not writing code. Upriver's AI agent runs that work across your warehouse, orchestrator and code, and hands your data engineers a validated fix to approve. Book a demo and see how your team's week comes back ->

Your senior data engineers spend the quarter on incidents, not the roadmap. Upriver's AI agent takes the data ops work off their plate: triage, root cause, validated fixes your team approves. Teams see roughly 80% fewer queued tasks. Book a demo ->

Your board wants AI on your data. Your AI keeps giving confident wrong answers. Upriver is an AI agent for data ops. It keeps the context behind your data current (which table is right, what changed and why) and runs the operational work that keeps it reliable: triage, root cause and validated fixes your team approves. Book a demo ->

Right now a stakeholder is more likely to find broken data than your team is. Upriver's AI agent watches what matters across your warehouse, orchestrator and code. It catches issues before the business does, and fixes them: a validated PR your team approves, before any stakeholder notices. See it in a 30-minute demo ->

Three morning alerts used to mean ~90 minutes of root cause analysis across tools. With Upriver, they became a few PRs approved in minutes. See it run on your stack ->