What does it take to build technology that works reliably at scale? ⚙️ At Digit 2026, our partner Wise brought the engineering conversation to both Tallinn and Tartu, sharing practical insights into the challenges behind large-scale systems. It all started on October 7 with Digit x WiseTalks, an official side event at the Wise office in Tallinn, where three platform engineers took a deep dive into real-world engineering challenges. • Fabio Hora explored how shared Java and JavaScript platforms can help teams manage dependencies securely and consistently across hundreds of repositories. • Mohammad Areeb Siddiqui shared how isolated AI sandboxes can give analysts the freedom to experiment while keeping sensitive data protected and AI interactions auditable. • Kristo Kuusküll examined how Wise manages consistency across microservices without relying on two-phase commit, using libraries instead of additional infrastructure. Two days later, the conversations continued at Digit 2026 in Tartu! Alongside meeting the engineering community at the Wise booth, Iya Roos, Data Scientist at Wise, took the Data & ML Stage with her talk "Beyond the Model: Operating Verification ML at Wise". Her session explored what it takes to keep verification ML reliable in production, from evaluating model updates and handling class imbalance to shadow mode testing and monitoring model behaviour in live traffic. From platform architecture to production ML, one thing stood out: building technology at scale means thinking beyond individual solutions and focusing on the systems that make them reliable. A big thank you to Wise and everyone involved for sharing their expertise, bringing the community together and being part of Digit 2026! 💜 #digitconf #digit2026 #PlatformEngineering #MachineLearning
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