Runtime vs Devin
Runtime is the agent harness for payment teams, with agents for operations work in your cloud. Devin, from Cognition, is an autonomous AI software engineer.
TL;DR: Runtime is the stronger choice for payment and risk operations teams, and runs coding agents like Claude Code and Codex alongside ops agents in your cloud. Devin is one of the most capable autonomous software engineers for modernization and migration work.
| Feature |  Runtime |  Devin |
|---|---|---|
| What it is | Agent harness for payment and risk ops | Autonomous AI software engineer |
| Users | Ops, risk, compliance, support, plus engineering | Engineering teams |
| Large code migrations | Possible with coding agents | Core strength |
| Operations workflows | Core use case | Not the focus |
| Choice of agent and model | Claude Code, Codex, OpenCode, any model | Devin |
| Runs in your cloud | Yes, or fully self-hosted | Enterprise deployment options |
| Approvals on money movement | Built in | Not applicable |
| Forward-deployed engineers | Payments domain experts | Cognition engineers |
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.
Devin is an autonomous AI software engineer from Cognition. Enterprises use it for large engineering programs like modernizing legacy code and migrating applications, often with Cognition's own engineers working alongside. Cognition crossed $1B in run-rate revenue in 2026.
Both are good products. 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 Devin makes sense
- The work is software engineering, especially modernization and migrations
- You want an autonomous engineer with vendor engineers alongside
- Your budget is the IT services line
- Users are engineering teams
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.