ElevenLabs Expands ElevenAgents With Spotlight for Enterprise Agent Optimization

ElevenLabs has expanded ElevenAgents into a broader enterprise automation platform built around the full lifecycle of an AI agent: defining workflow-driven behavior, testing changes, deploying across customer channels, and improving performance in production. The most recent addition, ElevenAgents Spotlight , monitors voice and chat conversations in real time and provides recommendations intended to help teams improve agent outcomes. In its official ElevenAgents Spotlight announcement , ElevenLabs describes Spotlight as an observation and improvement layer for production agents . It is designed to review every conversation, organize interactions by topic, evaluate quality against criteria written in plain language, and surface context-aware suggestions. Combined with Procedures, Experiments, and Versioning, the release set gives enterprises a more structured way to operate AI agents beyond initial deployment. Spotlight adds continuous production feedback Spotlight is aimed at a common operational problem with customer-facing AI agents: a system can appear ready in testing but encounter unexpected patterns, failure modes, or shifts in customer sentiment after it reaches live traffic. Rather than requiring teams to manually sample conversations, Spotlight analyzes production voice and chat interactions as they occur. The platform can automatically group conversations by topic and track metrics including success rate and sentiment . Teams can define evaluations in plain language to score the quality of interactions against their own standards. That matters because a useful agent evaluation may depend on a company's specific process, such as whether the agent followed an escalation policy or collected required information, rather than a single generic measure of response quality. Spotlight also includes anomaly detection for changes in key metrics. Its integration support for observability tools such as Datadog, Grafana, and OpenTelemetry means the agent data can fit in