Conversational AI agents for enterprise customer support across channels
Decagon builds AI agents that handle customer conversations over voice, chat, email and SMS for large brands. Its stack pairs contact-center telephony (Amazon Connect, Google Cloud Contact Center AI, WebSockets) with a streaming data layer (Kafka, Flink, ClickHouse, BigQuery), a sign that voice quality and real-time agent analytics are core engineering bets. Hiring is engineering-heavy and senior-skewed, with a sizable sales build-out alongside it.
Notable leadership hires: Account Director
Decagon is a San Francisco-based, privately held company founded in 2023 that develops a conversational AI platform for customer experience. Enterprises use it to deploy AI agents that resolve customer interactions across voice, chat, email, SMS and other channels, aiming to reduce reliance on traditional support tickets. The company employs 501–1,000 people and hires in the United States, United Kingdom, Australia, Canada and Gibraltar. Its teams span engineering, sales, product, research, operations, finance, HR and security.
Decagon runs on Python and TypeScript across AWS and GCP, with Kubernetes, Docker and Terraform. Its data layer uses Kafka, Apache Flink, Airflow, dbt, ClickHouse and BigQuery, and voice runs on Amazon Connect and Google Cloud Contact Center AI.
Yes. Engineering is Decagon's largest hiring area, weighted toward senior talent, with sales, product and research also active. Roles are open in the US, UK, Australia, Canada and Gibraltar.
Decagon is building an AI agent development playbook, integrations with customer systems, self-serve agent configuration, and monitoring and analytics for deployed agents, plus internal deal and pricing processes.
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Decagon's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.