Runtime vs Runbear
Runtime is the agent harness for payment teams, with agents that investigate on their own computers in your cloud. Runbear is a no-code way to put AI agents in Slack and Teams.
TL;DR: Runtime is the stronger choice for payment and risk operations, where agents investigate on their own computers, touch sensitive data in your cloud, and need approvals and an audit trail. Runbear is a fast, no-code way to answer questions in Slack and Teams.
| Feature |  Runtime |  Runbear |
|---|---|---|
| What it is | Agent harness for payment and risk ops | No-code AI agents in Slack and Teams |
| Setup speed | Days with a forward-deployed engineer | Minutes, no-code |
| Slack and Teams | Built in, plus email, SMS, and voice | Core product |
| Each agent gets its own computer | Yes: browser, terminal, files | No |
| Runs in your cloud | Yes, or fully self-hosted | Hosted platform |
| PCI and PII handling | Masking, local open models | General |
| Approvals on money movement | Built in | Not the focus |
| Audit trail | Every query, tool call, approval, and cost | Conversation history |
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.
Runbear is a no-code platform for building AI agents that live in Slack, Microsoft Teams, and Discord. Agents answer questions from tools like Notion, Linear, and HubSpot, automate requests in shared channels, and can be set up in minutes without engineering.
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 Runbear makes sense
- You want AI answers in Slack or Teams in minutes, without engineering
- The work is mostly Q&A and lightweight requests
- Your data lives in common SaaS tools
- Sensitive financial data isn't involved
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.