ChooChoo
ChooChoo Works, Inc. · Productivity
ChooChoo is an AI agent governance platform for coding agents. Its runtime sits in the path of every session, scores the risk in each action, and logs a tamper-evident receipt for auditing.
About ChooChoo
What Is ChooChoo
ChooChoo is an AI control plane for coding agents, built by ChooChoo Works, Inc. It targets engineering, security, privacy, and legal teams that already run AI coding agents in production and now need to control what those agents do. The product calls itself a risk signal box: a runtime that watches every agent action, decides whether it fits policy, and writes a record that later can't be quietly changed.
The problem it solves is trust. Observability tools show what an agent did after the fact. ChooChoo tries to govern what happens while it happens. Budgets, model access, and policy-as-code rules get enforced at the gateway, before an agent writes a line or touches a system. That shift from post-mortem review to live enforcement is the core claim of the product.
The main limitation is scope. ChooChoo is aimed at teams running coding agents such as Claude Code, Codex, Copilot, and Gemini, not at general consumer chat. A solo user who just wants one agent to answer questions will find it heavier than needed, and the free local CLI doesn't change that.
Getting Started
- Install the CLI, which drops the
choochoobinary on your machine, or grab the desktop app for macOS, Windows, or Linux. - Point the runtime at the coding agents you already use and let it read a session.
- Review the recorded session in the local viewer to see actions, tool calls, and risk flags.
- Write policy-as-code rules for budgets, model access, and allowed tools.
- Turn on enforcement at the gateway so risky actions are blocked before they run.
Product Information
A quick look at ChooChoo's pricing, supported platforms, and performance.
Best for
The users, tasks, and scenarios where this tool fits best.
Users
- Engineering teams running coding agents
- Security and privacy teams
- Legal and compliance staff
- Individual developers
Tasks
- Enforcing spend limits on agents
- Restricting model and tool access
- Auditing an agent session
- Keeping agent configs in sync
Scenarios
- Rolling out coding agents across a company
- Passing a security review
- Catching a risky action before it ships
- Onboarding a new agent tool
Key features
In-Path Runtime With Tamper-Evident Receipts
The runtime runs in the path of every agent, not off to the side. It intercepts each action, evaluates the risk, and produces a receipt that is designed to be tamper-evident. If someone later edits the record, the change shows up. That's what makes the output usable as evidence in a review.
Policy-as-Code Enforcement at the Gateway
ChooChoo enforces budgets, model access, and policy rules at the gateway, before an agent writes a line. You express the rules in code, so they live in version control and change like any other config. The pitch is governance at the gate rather than governance at the audit.
One Gateway for Every Agent
Coding agents multiply fast, and each one tends to ship with its own logging. ChooChoo routes every AI coding session through the same gateway no matter which agent your team uses. Claude Code, Codex, Copilot, and Gemini sessions land in one place, which keeps rules and records consistent.
Local Viewer and Desktop App
A free desktop app for macOS, Windows, and Linux acts as a local viewer for agent sessions. You can record, review, and improve a session without sending data anywhere first. For a single developer, this is the whole product, and it costs nothing.
Drift Detection With Pull Requests
ChooChoo generates and maintains context files, rules, and agent configs. When it spots drift between what is configured and what the agent is doing, it opens a pull request instead of silently correcting things. Agents get to improve with every cycle while humans still approve the change.
Free CLI, Paid Runtime for Teams
The local CLI is free and the company says it will stay free, so any team can govern agents without a procurement cycle. Paid plans center on the hosted or self-hosted runtime that delivers enforcement and central records across a whole fleet.
Pros and cons
Pros
- The runtime works in the path of agents from several vendors, so governance stays consistent across Claude Code, Codex, Copilot, and Gemini.
- Tamper-evident receipts turn agent activity into audit-ready evidence rather than a pile of raw logs.
- Policy-as-code rules for budgets and model access are enforced before an action runs, not reviewed afterward.
- The CLI and desktop viewer are free, which lowers the cost of trying governance on a single machine.
Cons
- The product targets teams running coding agents, so casual users who want a general chat tool will find it overbuilt for their needs.
- Because enforcement happens at the gateway, the value depends on routing your agent traffic through ChooChoo, which is extra setup.
- Public pricing for the team runtime isn't published, so buyers have to book a call to get numbers.
- Self-hosted and hosted options add operational work that a small team may not want to take on.
Frequently asked questions
It governs AI coding agents. A runtime sits in the path of each agent session, checks every action against your policy, scores the risk, and writes a tamper-evident receipt. The goal is to control what agents do while they work, not only to review it later.
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