Tenor

Tenor is a platform for building and running AI native service businesses. It is aimed at domain experts who want to start a company where AI agents perform the bulk of the work, and at organizations that want AI work to be visible, governed and accountable rather than scattered across private chats and disconnected automations. The company states that it is backed by Y Combinator. The product is described as the system around the model, in three layers. Context is a company data layer that holds data, knowledge, decisions and outcomes. Execution is a harness and workflow layer with tools, memory, instructions and end to end work. Governance is a set of checkpoints and controls such as rubrics, permissions, approvals and exceptions. A continuous improvement loop retrieves context, applies a rubric, acts within bounds, records the outcome and updates what happens next. The site gives a sales example in which the system recommends a next best action for a lead based on prior decisions and outcomes, and says privacy safe patterns from one deployment can strengthen recommendations in others. Its mission page argues that AI needs a role, a manager, a budget, guardrails and persistent memory, so that AI spend can be tied to completed work and measurable outcomes. Access is by request through the website. No pricing is published.