Benten

Using Docker Compose to clone and run Benten locally is straightforward. It is reassuring that the company does not run a cloud service, ensuring you own the observability stack without giving them your call audio.

The focus on latency metrics is precise. However, the self-hosted requirement means you must manage the infrastructure yourself.

Benten provides a robust framework for understanding the nuances of Voice AI conversations. The distinction between what the transcript says and what the customer actually hears is critical; measuring the silence and interruptions reveals issues that standard API dashboards miss. The ability to sit above providers like ElevenLabs and Retell allows for a unified timeline of truth. Since it is self-hosted and open source, teams can inspect exactly how metrics like turn latency and dead air rate are calculated. This independence is valuable for debugging the subtle bugs that make calls feel awkward, such as barge-ins or speech overlap, which logs often ignore.

The approach Benten takes to Voice AI observability is refreshing. By focusing on rhythm, latency, and dead air rather than just transcripts, it addresses the actual customer experience. Being MIT licensed and self-hosted ensures there is no lock-in, and the ability to clone the repo to run locally is a significant advantage for engineering teams who want full control over their voice data and metrics.

Benten offers an interesting independent layer above providers like Vapi, yet its self-hosted nature means you manage the infrastructure yourself. It is a useful tool for comparing vendor metrics, though the lack of a managed service might be a barrier for smaller teams.