Sikaru: self-improving agents, with the lab built in (www.sikaru.ai)

Sikaru has been launched as a comprehensive platform for AI agents, integrating inference, managed agents, and a testing lab into a single cohesive environment. It allows teams to utilize their existing production data for continuous improvement, effectively turning each operational run into a training opportunity. By automating aspects of training and evaluation, Sikaru enables teams to focus on defining success criteria rather than infrastructure maintenance. This shift in approach signifies an essential evolution in how AI agents learn and improve, prioritizing real-world interactions over manual coding. By providing each agent with its own learning lab that tracks performance and adapts to feedback, Sikaru streamlines the traditional development process, which often sees redundant infrastructure across multiple teams. With features like managed sandboxes, seamless model updates, and comprehensive logging, Sikaru helps reduce the time and complexity involved in getting production agents live. The platform’s built-in capability to learn from each operation ensures that improvements are proactive and aligned with user behavior, positioning Sikaru as a pivotal tool for the future of AI/ML development in effectively managing and enhancing agent performance.