Decagon
by Decagon · San Francisco, USA · Founded 2023
Enterprise support agents with deep QA tooling
Overview
Decagon competes directly with Sierra for large support deployments and differentiates on operational tooling rather than raw capability. Its Agent Operating Procedures let support leaders express handling rules in plain language, and its QA and analytics layer shows exactly why an agent answered as it did — which is the difference between an agent you tune and one you argue with. It handles chat, email and voice, integrates with major helpdesks, and takes actions in connected systems. Pricing is quote-based and lands in the same six-figure band as Sierra, and it likewise sits on top of an existing helpdesk rather than replacing it.
Our verdict
The best choice when you have support operations people who will actively tune the agent, because the QA and audit tooling is genuinely ahead of Sierra's. If nobody will own that work, you are paying a premium for capability you will not use.
Best for
High-volume support teams with operations staff who will actively tune and audit the agent.
Avoid if
Nobody will own agent tuning — the tooling advantage disappears.
Pros
- Best-in-class QA and behaviour auditing tooling
- Plain-language operating procedures support leads can write
- Strong startup and mid-market references, not just enterprise
Cons
- Six-figure annual commitments
- Requires a separate helpdesk underneath
- Value depends on having someone to tune the agent
Key capabilities
Frequently asked questions
How much does Decagon cost?
Decagon does not publish pricing. Third-party data puts contracts roughly between $95,000 and $590,000 per year, quoted by resolution volume under an annual commitment.
Decagon or Sierra?
Decagon has stronger QA and auditing tooling, so it suits teams who will actively tune the agent. Sierra is stronger on bespoke brand-tuned design and action-taking in complex enterprise systems.
What are Agent Operating Procedures?
Decagon's mechanism for writing handling rules in plain language rather than code, so support leaders — not engineers — can define how the agent should behave in specific situations.