Runtime vs Decagon
Runtime is one agent harness for every payment team, including support. Decagon builds AI agents for customer support.
TL;DR: Runtime is the stronger choice when support is one of several teams you want on agents, so a "where's my payout" ticket, the payment ops trace, and the recon break share one investigation. Decagon is a strong, purpose-built AI agent for customer support conversations.
| Feature |  Runtime |  Decagon |
|---|---|---|
| What it is | Agent harness for every payment team | AI agents for customer support |
| Customer conversations | Slack, Teams, email, SMS, voice | Purpose-built for chat, email, and voice |
| Teams covered | Support, payment ops, finance, risk, compliance | Customer support |
| Escalations into the ledger and processor | Agents investigate end to end | Hand off or call configured actions |
| Shared memory across teams | One governed memory | Within support |
| Runs in your cloud | Yes, or fully self-hosted | Hosted platform |
| Approvals on money movement | Built in | Configured actions |
Two different jobs
Runtime is the AI agent harness for payment teams. From payment ops to risk, compliance, and support, anyone on the team can build agents that work their queues on their own computers inside your cloud, called from Slack, Teams, email, SMS, or voice, with approvals and a full audit trail.
Decagon builds AI agents for customer support. Its agents answer customers across chat, email, and voice, follow support procedures, and hand off to people, with analytics on conversation quality and resolution.
The right one depends on the work you're trying to hand off.
Why payment teams choose Runtime
Built for money movement
Payment work is mostly exceptions: a held payout, an ACH return with an odd code, a dispute where the evidence contradicts the claim. Runtime agents reason through those cases on their own computers, across your ledger, processor, bank files, and tickets, and stop for a person before anything moves money.
Your data stays yours
Agent computers run in your AWS, GCP, or Azure account, or you self-host the whole platform. Card numbers, SSNs, and secrets are masked before any prompt or log, and you can serve open-weight models locally for PCI and PII work.
One harness for every team
Support, payment ops, finance, risk, and compliance all build on the same harness, so one stuck payment is one investigation, not four. Every run is stored with its evidence, approvals, and cost, ready when an auditor or sponsor bank asks.
An engineer, not an account executive
A forward-deployed AI engineer who has built payment infrastructure maps your processes, builds the first agents with your team, and sets up guardrails.
When Decagon makes sense
- Customer support is the only team in scope
- You want an out-of-the-box support agent across chat, email, and voice
- Conversation analytics for support leaders is a priority
- Investigations rarely need data beyond the help desk
When Runtime makes sense
- You run payments, banking, or lending operations and the queue keeps growing
- The work needs judgment on exceptions, not just a fixed sequence of steps
- Card data or PII has to stay in your environment
- You need approvals on money movement and an audit trail your sponsor bank will accept
- You want one platform for every team that touches a transaction
See Runtime on your busiest queue
Bring one SOP. A forward-deployed AI engineer builds the first agent with your team, inside your cloud.