Agentlens, an SDK that shows whether your AI features are working by customer (agentlens-demo-omega.vercel.app)

AgentLens has launched a groundbreaking SDK designed to enhance the transparency and accountability of AI features in SaaS applications. Unlike traditional analytics tools that aggregate data and overlook individual user struggles, AgentLens provides account-level insights into AI interactions, pinpointing issues such as high abandonment rates and low user satisfaction before they lead to churn. For instance, it reveals that while a product may show green in uptime metrics, over 54% of interactions may end in user abandonments, indicating a lack of quality that conventional monitoring fails to capture. This new tool captures real-time data on AI interactions, including user inputs, output quality, and follow-up actions. This level of detail allows engineering teams to respond rapidly to performance issues and quality regressions, providing alerts on specific problems within hours instead of weeks. Meanwhile, customer success teams receive daily digests highlighting accounts in distress and urgent renewal scenarios. By focusing on the unique challenges of AI feature observability, AgentLens promises to significantly improve the management and effectiveness of AI implementations in products, ultimately leading to better customer retention and satisfaction.