Decagon

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Decagon builds enterprise AI agents for customer support, positioning them as an AI concierge that resolves issues end to end rather than a chatbot that only suggests articles. Its agents handle conversations across chat, email, voice, and SMS, drawing on a company's knowledge bases, help articles, product documentation, past conversations, and internal policies to answer accurately, and escalating to a human with full context when a request falls outside what they should handle. The centerpiece of the platform is what Decagon calls Agent Operating Procedures, or AOPs. Instead of building rigid coded decision trees, customer-experience teams write support workflows in plain language, when to issue a refund, when to escalate, how to handle a particular complaint, and Decagon compiles those instructions into executable agent logic. The effect is a division of labor: CX operators own the business logic and can change agent behavior without waiting on an engineering sprint, while engineers manage the underlying integrations and guardrails. Crucially, AOPs trigger real backend operations, so an agent can retrieve and update customer data, process a refund, cancel a subscription, or query a third-party system, not just talk. Decagon unifies its channels under one intelligence layer with cross-channel memory, so an agent recognizes a returning customer and recalls earlier issues, and a conversation that starts in chat can continue by voice without the customer repeating themselves. Its voice agents handle real-time calls with interruption handling and brand-matched voices, and can also run outbound calls for things like renewals and follow-ups. Increasingly the company routes traffic through language models it has trained in-house on customer-support interactions, alongside leading foundation models. For the teams operating these agents, Decagon adds tooling for reliability and oversight: monitoring and quality assurance, guardrails, a trace view that shows how a given procedure executed for a specific conversation, and tools that help debug and draft new procedures. It is an enterprise-focused, managed offering, deployed with the help of Decagon's own product managers and engineers rather than through self-serve signup, and priced around resolved conversations rather than per agent seat, aimed at large support operations in sectors like fintech, retail, travel, and consumer technology.