Building AI Agents: Why reliable communications data matters

AI agents are increasingly being integrated into real products, but their effectiveness is often hampered by unreliable data rather than faults in the models themselves. The inconsistency, incompleteness, and lack of safety of communications data, such as emails and calendar entries, present significant challenges, as these data sources vary in schema and behavior across different providers. This can lead to gradual system failures, not through dramatic outages but through accumulating inaccuracies and inefficiencies. As AI adoption accelerates, infrastructure readiness lags, creating a gap that needs addressing by normalizing data and enforcing strict access controls to ensure reliable operations. Nylas addresses these issues by providing a stable communications infrastructure that normalizes data across email, calendar, and meeting platforms, ensuring consistent schemas, reliable event delivery, and robust security measures. This infrastructure enables AI systems to function correctly without introducing governance or privacy risks, highlighting the importance of focusing on data reliability and infrastructure over model sophistication in AI development.

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