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ForgeCode

Your software factory. It never clocks out

Pricing
Paid
Small, Medium, Large, Ultra, Enterprise

About ForgeCode

ForgeCode is an AI agent platform, described as a software factory, that turns GitHub issues, Slack threads, alerts, or a prompt into tested, shipped code changes. It is built for engineering teams that want whole roles and long-running programs handled continuously rather than single coding tasks.

A trigger such as a Slack mention or an alert opens a mission that splits into issues; agents write and test code, rework failing tests, and restart from a checkpoint if a factory crashes, before a pull request lands back where the work started, with a staged demo and checks passed.

Teams run whole roles on a factory, including on-call and bug triage, spec-to-feature delivery, migrations, QA and tests, CI and dependency upkeep, security fixes, releases, performance budgets, documentation and SDKs, tech debt, and accessibility. ForgeCode supports 300+ model providers with bring-your-own keys, or its own optimized model gateway.

ForgeCode runs on its own cloud or on a customer's own AWS, Google Cloud, or Azure account under Bring Your Own Cloud. Pay-as-you-go pricing starts at $0.20 per agent-hour on a Small machine, scaling to $1.60 on an Ultra machine, while Enterprise adds organizations and teams, SAML SSO, custom usage limits, and a forward-deployed engineer.

Use cases

  • Resolving on-call alerts with root cause and guardrails
  • Triaging and fixing reported bugs
  • Turning a spec into a shipped, monitored feature
  • Running large migrations without a code freeze
  • Patching security advisories across every repo

Key features

  • Converts triggers like Slack, GitHub issues, or alerts into shipped PRs
  • Splits a mission into parallel issues
  • Self-recovers from crashes via checkpoints
  • Automated root-cause analysis for production alerts
  • Bring your own cloud and model keys
  • Supports 300+ model providers
  • Automated changelog and canary release rollout
  • Regenerates SDKs and docs when an API changes
  • Does not train AI models on customer code or data
  • Live dashboards and executive summaries

Pros and cons

Pros

Does not train AI models on customer code or data
Resumes automatically from a checkpoint after a crash
Supports 300+ model providers out of the box

Cons

Automations, artifacts, and reports are limited on the pay-as-you-go plan
Bring Your Own Cloud and multi-person organizations require the Enterprise plan

Pricing

Small
$0.20
  • 2 vCPU / 8 GB RAM / 128 GB disk
  • Bring your own keys for 300+ model providers
Medium
$0.40
  • 4 vCPU / 16 GB RAM / 256 GB disk
Large
$0.80
  • 8 vCPU / 32 GB RAM / 512 GB disk
Ultra
$1.60
  • 16 vCPU / 64 GB RAM / 1024 GB disk
Enterprise
Custom
  • Bring your own cloud (AWS, Google Cloud or Azure)
  • Organisations and teams
  • SAML SSO
  • Forward-deployed engineer

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Frequently asked questions

What is an agent-hour?
One hour of one agent running in a factory, billed separately at the hourly rate of the machine size chosen.
Which machine size do I need?
Start with Small, and move to Medium, Large, or Ultra as builds, test suites, or services need more CPU, memory, or disk.
How is model usage billed?
Either bring your own keys for a supported provider that bills directly, or use the ForgeCode gateway's optimized models at API pricing from prepaid credit.
Can I run factories in my own cloud?
Yes, on Enterprise, Bring Your Own Cloud runs factories in a customer's own AWS, Google Cloud, or Azure account.
What is a forward-deployed engineer?
Part of Enterprise support: an engineer from the ForgeCode team who works with the customer on their business domain and keeps optimizing the factory.
Do you train AI models on my data?
No, customer content including code, files, prompts, conversations, and outputs is not used to train AI models.

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