Million Software, Inc.

Million Software, Inc. builds verification for AI coding agents, helping developers prove AI-generated code actually works.

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Overview

Million Software, Inc. is a developer-focused product built around verification for AI coding agents. The homepage says the company is solving the problem of proving that code generated by AI actually works, which places the product in the software verification and developer tooling category.

The public site does not provide a detailed feature list, pricing model, or documentation set in the supplied evidence. What is clear is the product’s intended purpose: help teams move from AI-generated code to code they can verify with more confidence, with the company positioning itself as a team experienced in building production software and open-source tools.

What Million emphasizes

Verification for AI-generated code

The homepage positions Million around verification for AI coding agents, with the goal of proving that generated code actually works rather than assuming it is correct.

Focus on correctness

The site describes the product as solving “the hardest problem in AI coding,” which suggests the core workflow centers on validating code quality and correctness.

Production experience

Million says the team has built tools that run for millions of users in production, which indicates experience with production-grade developer tooling.

Developer-tooling background

The homepage references prior open-source work and React virtual DOM performance work, which gives some context for the team’s developer-tooling background.

Direct founder contact

The site invites founders to reach out directly, suggesting an early-stage product that may involve direct contact rather than a fully self-serve flow.

Where Million may fit

Validate AI-generated code
Teams building with AI coding agents can use a verification layer to check whether generated code behaves as intended before it reaches users.
Evaluate AI coding workflows
Founders or engineering leads evaluating AI-assisted development workflows can use Million as part of a code-correctness review process.
Support production delivery
Developer teams shipping production software can use a verification-focused tool to reduce the gap between code generation and real-world reliability.
Work with the team directly
Early adopters who want to discuss their workflow directly with the company can reach out to the founders rather than waiting for a fully documented self-serve setup.

Pros and Cons

Pros

Clear positioning around a specific developer problem: verifying AI-generated code.
The homepage connects the product to production software experience and prior open-source work.
The site makes it easy to contact the founders directly.
The pricing URL is publicly visible even though the page is unavailable, which suggests the product has a dedicated pricing path or planned pricing page.

Cons

The public pages do not describe concrete features, integrations, or supported workflows in detail.
The pricing page currently returns a 404, so pricing and plan structure are not available from the supplied evidence.
The site appears to rely on direct contact for interest, which may indicate limited self-serve information.

FAQ

What is Million for?

Million’s site says it is building verification for AI coding agents, but the public pages do not spell out setup steps or supported integrations.

How do teams get started?

The source material does not describe a public self-serve onboarding flow. The site ends with a contact address for founders and does not list a documented signup process.

What does the product verify?

The available pages do not describe outputs in detail. Based on the homepage copy, the product is aimed at proving that code produced by AI actually works.

Is pricing published?

The source does not provide a pricing table or plan details. The pricing URL currently returns a 404 page not found message.

What integrations or platforms are supported?

The homepage frames Million around AI coding agents and verification of generated code, but it does not list specific platform support, SDKs, or documentation links in the supplied evidence.