The US cloud-based software company, Salesforce and its Research AI department, have unveiled eVerse, a new environment designed to train voice and text agents through synthetic data generation, stress testing and reinforcement learning.
In an aim to resolve a growing reliability problem known as jagged intelligence, where systems excel at complex reasoning yet falter during simple interactions.
The company views eVerse as a key requirement for creating an Agentic Enterprise, where human staff and digital agents work together smoothly and dependably.
eVerse supports continuous improvement by generating large volumes of simulated interactions, measuring performance and adjusting behaviour over time, rather than waiting for real-world failures.
A platform that played a significant role in the development of Agentforce Voice, giving AI agents the capacity to cope with unpredictable calls involving noise, varied accents and weak connections.
Thousands of simulated conversations enabled teams to identify problems early and deliver stronger performance.
The technology is also being tested with UCSF Health, where clinical experts are working with Salesforce to refine agents that support billing services. Only a portion of healthcare queries can typically be handled automatically, as much of the knowledge remains undocumented.
eVerse enhances coverage by enabling agents to adapt to complex cases through reinforcement learning, thereby improving performance across both routine and sophisticated tasks.
Salesforce describes eVerse as a milestone in a broader effort to achieve Enterprise General Intelligence. The goal is a form of AI designed for dependable business use, instead of the more creative outputs that dominate consumer systems.
It also argues that trust and consistency will shape the next stage of enterprise adoption and that real-world complexity must be mirrored during development to guarantee reliable deployment.
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