Pricing
Two ways to buy a software factory
Self-serve gets you a working factory today: $99 per user per month, with model usage billed as you go. Enterprise is a forward-deployed engagement: we build the factory inside your infrastructure, cloud or on premises, and run it on your backlog for the first one to three months.
Self-serve
$99per user, per month
The platform fee. Model usage is billed separately, as you use it: three ways to pay for it below.
- Claude Code, Codex, or Grok Build, picked per task
- Isolated cloud sandboxes, repo checks before every PR
- Recorded browser QA on UI changes
- One pull request per changed repo
- Cancel anytime
Enterprise
Customquoted in writing during scoping
Your own factory, built and operated by forward-deployed engineers until your team takes the controls.
- Runs in your cloud, or fully on premises
- Customized harnesses, integrations, and credential mapping
- FDE-led: the first one to three months run on your backlog
- Ongoing maintenance and upgrades under subscription
Model usage
How model usage is billed
The $99 covers the platform, not the AI. Model usage is paid one of three ways.
01
Metered, the default
Nothing to configure. Usage is billed at each provider's published token rates and itemized on your monthly invoice. No markup.
02
Your API keys
Add your Anthropic, OpenAI, Azure OpenAI, xAI, or Moonshot key. The provider bills you directly; FactoryKit charges nothing for models.
03
Your Codex subscription
Connect a ChatGPT plan with Codex and Codex tasks run on it, covered by what you already pay OpenAI.
Claude Code subscriptions can't be attached to outside products, so Anthropic models run on your API key or the metered default.
Enterprise
The best engineering orgs already run one
Ramp and Uber assigned platform teams to build internal coding-agent factories; those systems now produce a major share of their merged code. That is the result you are buying, without staffing a platform team to get it.
Build it in-house
- A platform team, staffed for quarters
- Months before the first merged PR
- Yours to maintain as models change
FactoryKit engagement
- Operators arrive with the factory
- Verified PRs in week one
- Handed to your team, maintained under subscription
The engagement
How a forward-deployed engineering engagement works
01 · Week 0
Demo
Watch the factory clear a real task from one of your repos, live, in 30 minutes.
02 · Months 1 to 3
Embed and run
Our engineers drive the factory on your backlog while it is being built on your infrastructure.
- Intake wired to Linear or Jira
- Verified PRs land every week
- Delivery reports against agreed outcomes
03 · Handover
Hand over
Your engineers take the controls: your cloud, your integrations, your credential mapping, your models if you want them.
04 · Ongoing
Operate
We maintain, upgrade, and tune the factory under an ongoing subscription. It keeps improving after we leave.
FAQ
Questions engineering leaders ask
What does the self-serve plan include?
The $99 per user per month covers platform access: tasks against your connected GitHub repos, isolated sandboxes, recorded browser QA, and pull requests as the output. It is not an AI allowance; model usage is billed separately, one of three ways. You can cancel anytime.
How do we pay for model usage?
Three ways. Default: FactoryKit meters your usage and bills it at each provider's published token rates, itemized, with no markup. Or add your own API key (Anthropic, OpenAI, Azure OpenAI, xAI, or Moonshot) and the provider bills you directly. Or connect a ChatGPT plan with Codex and Codex tasks run on that subscription. Claude Code subscriptions can't be attached to outside products, so Anthropic models use an API key or the metered default.
What is a forward-deployed engineer (FDE)?
A forward-deployed engineer is an engineer who embeds with a customer to deploy and adapt a product inside the customer's own environment, rather than supporting it from the outside. FactoryKit engagements are FDE-led: our engineers install the factory on your infrastructure, run it against your backlog for the first one to three months, and hand it over to your team.
Can we run FactoryKit on premises?
Yes, as an enterprise engagement. The factory is deployed inside your infrastructure, in your cloud or fully on premises, and customized to your workflow: your integrations, your credential mapping, and your models if you want them.
What happens after the one to three months?
Your team runs the factory; we stay on maintenance and upgrades under the subscription. The engagement is designed to end. The factory is not.
Why is there no enterprise price list on this page?
Because there is no standard enterprise deployment. The factory runs on your infrastructure with your integrations, so rates and scope are quoted in writing during scoping, before you commit to anything. The standard deployment is the self-serve plan, priced above.
Does our code or our credentials ever leave our infrastructure?
On an enterprise deployment the factory runs in your cloud or on premises, and credential brokering keeps secrets out of the sandboxes entirely: agents do their work without ever holding a real key. On the self-serve plan, tasks run in isolated sandboxes with the same credential brokering.
What does the ongoing subscription cover?
Maintenance, upgrades, new agent harnesses as models improve, and support. Your factory keeps getting better without a re-engagement.
See it run on your repo
Book 30 minutes and watch FactoryKit clear a real ticket from your repo, live. We will scope your engagement while it runs.