Runtime vs Factory: AI Agents for Fintech Ops vs Code

Feature	Runtime	Factory
What it is	Agent harness for payment and risk ops	AI agents for software engineering
Users	Ops, risk, compliance, support, plus engineering	Software engineers
Software engineering depth	Runs Claude Code, Codex, and OpenCode	Purpose-built Droids across the SDLC
Operations workflows	Core use case	Not the focus
Non-engineers build agents	Yes, from plain English and SOPs	Engineer-facing
Runs in your cloud	Yes, or fully self-hosted	Enterprise deployment options
Approvals on money movement	Built in	Not applicable
Payments domain depth	Processor codes, bank files, network rules	General software

Factory is the better fit for engineering organizations that want autonomous Droids across the software lifecycle: implementation, testing, review, and migrations. Runtime is the better fit for the payment ops, risk, compliance, finance, and support teams that run the business on top of that software. Runtime is the AI agent harness for payment and fintech teams, with approvals before money moves, an audit trail, and agents that run in your own cloud.

Factory and Runtime at a glance

Factory builds Droids, AI agents that implement, test, review, and maintain software across the development lifecycle. Large engineering organizations use them for migrations, code review, documentation, and incident response, from the IDE, CLI, Slack, or Linear.

Runtime is the AI agent harness for payment and fintech 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.

Factory is for engineering organizations shipping software. Runtime is for the payment, risk, and finance teams that run the business on top of it.

How they differ

Fintech operations, not the SDLC

Droids are tuned for the software lifecycle. Runtime agents are built for money movement: processor reason codes, ACH returns, bank files, network rules, reserves, and settlement. The users are ops analysts writing SOPs, not engineers writing tickets.

Bring your own cloud, sandbox, and models

Runtime runs agent computers in your AWS, GCP, or Azure account, or fully self-hosted via Helm. You can use your own sandbox provider and any model, including open-weight models served in your cloud for PCI and PII work.

Harness and model routing

Runtime routes work across Claude Code, Codex, and OpenCode and across models, with fallbacks when a provider goes down. Engineering can use the same harness for coding tasks while ops teams run their agents on it.

Guardrails and an FDE who knows payments

Ops agents act on money, so Runtime agents start read-only, ask for approval before anything moves money, and record every query, tool call, approval, and cost. A forward-deployed engineer with a payments background maps your processes and builds the first agents with your team.

Where Runtime enters the picture

Runtime is the AI agent harness for payment and fintech teams. Factory makes engineers faster, and it leaves the operations queues alone. When a payment company wants agents there, the usual alternative is building an internal platform: isolated computers, scoped credentials, RBAC, approvals, an audit trail, evals, and model routing with fallbacks. That is two quarters of engineering before the first agent touches real data, competing with the product roadmap Factory is helping you ship.

Take a merchant asking why a payout is late. Support has the ticket, payment ops has to trace it in the processor, and finance sees the gap in reconciliation. On Runtime one agent pulls the ticket, the processor events, and the ledger entries, finds the ACH return behind the delay, and drafts the reply and the fix for a person to approve. One investigation, one record, across all three teams.

No single vendor to depend on. Agent computers run in your AWS, GCP, or Azure account or fully self-hosted, on your own sandbox provider with fallbacks. Work routes across Claude, GPT, Gemini, and open-weight models, and across Claude Code, Codex, and OpenCode.
Guardrails you set. Read-only by default, approvals before money moves, RBAC, masked credentials, PII and PCI stripping, and every run recorded end to end.
Built for teams. Shared agents, templates, and one memory across support, payment ops, finance, risk, and compliance.
An engineer, not an account executive. A forward-deployed AI engineer who built payment systems at Hulu's payments team at Disney, Finix, Modern Treasury, or BlackRock maps your processes and builds the first agents with your team.

New agent

Create a banking ops agent that handles RFIs, hold-harmless requests, and returns of funds from our partner bank, verifies against our ledger, and drafts replies for my approval.

Describe the agent you want

Agent ready

bank-ops-agent

Tools picked from your prompt

EmailLedgerSFTPMastercard

Anyone on the team describes the work in plain English and attaches the SOP. Runtime builds the agent and gives it its own computer.

Where Factory is stronger

Software engineering depth. Purpose-built Droids across implementation, testing, review, and maintenance.
Engineering workflows. Migrations, code review, documentation, and incident response.
Developer surfaces. Works from the IDE, CLI, Slack, and Linear.
Large engineering organizations. Built for engineering productivity at scale.

Which should you choose

Choose Factory if

Your users are software engineers
The work is code: features, migrations, reviews, incidents
You want agents across the full development lifecycle
Engineering productivity is the primary goal

Choose Runtime if

Your users are payment ops, risk, compliance, finance, and support teams
Agents need to work your ledger, processor, and bank data in your cloud
You want harness and model routing instead of one vendor's agent
You need approvals on money movement and an audit trail your sponsor bank will accept

See Runtime on your busiest queue

Bring one SOP. A forward-deployed AI engineer builds the first agent with your team, inside your cloud.

Book a demo

Frequently asked questions

Is Factory good for fintech companies?

Factory is a strong choice for fintech engineering teams that want agents across the development lifecycle. Its Droids are built for software engineers. Runtime is built for the operations teams around the code: payment ops, risk, compliance, finance, and support.

Can non-engineers use Factory or Runtime?

Factory is engineer-facing. On Runtime, ops analysts build agents from their SOPs in plain English, while engineering controls credentials, access, and any code the agents write.

What is the best Factory alternative for payment operations teams?

For payment operations work like held payouts, ACH returns, disputes, and recon breaks, Runtime gives ops teams agents that investigate across your ledger and processor, with approvals before money moves and a full audit trail.

Can Runtime run in my own cloud with my own models?

Yes. Runtime agent computers run in your AWS, GCP, or Azure account, or fully self-hosted, with your own sandbox provider and any model, including open-weight models served in your cloud.

Where does Runtime fit next to Factory?

Factory gives software engineers agents for the development lifecycle. Runtime is the harness where payment and fintech operations teams build agents from their SOPs and run them in your cloud, with approvals before money moves and every run recorded. Engineering can keep Factory for code while operations runs on Runtime.