Decagon builds AI agents for customer service. Companies connect it to their help center, policies, and internal systems, and the agent answers questions, looks up orders, processes refunds, and handles account changes. It aims to resolve the issue instead of only deflecting people to articles.
A key idea is that support teams control the agent without engineers. They write instructions in natural language, called Agent Operating Procedures, that define how to handle scenarios, which keeps the behavior consistent and reviewable. Testing and monitoring tools show how the agent performs, and analytics highlight why customers contact support.
Decagon sells to consumer-facing businesses with high ticket volume, often on pricing tied to conversations or resolutions. Quality depends on connecting the agent to accurate data and careful setup. Competitors include Sierra, Intercom Fin, Zendesk AI agents, Ada, and Forethought. Decagon suits support teams that want to automate a large share of tickets.