Million
Million open-sources React Doctor (15k stars) and React Scan (22k stars), and is building ReactBench to check AI-written React before it ships.
Install React Scan and React Doctor today — they're free, open source, and built by a team that clearly understands the React runtime, with 22k and 15k GitHub stars respectively as evidence other React developers reached the same conclusion. React Scan finds rendering and performance problems; React Doctor diagnoses issues across a codebase. If your React shop already runs Cursor or Copilot, these tools are an easy addition regardless of where the benchmark lands. Treat ReactBench, the custom datasets and the RL environments as a watching brief, not a procurement decision: Million describes them as things it builds, and the public homepage offers contact rather than a purchasable product.
Verified 3d ago · liveness 62/100 · cite: rightaichoice.com/tools/million
- React teams wanting runtime and rendering checks beyond static lint rules
- Engineering teams running AI coding agents that need code review help before merge
- Agent builders evaluating coding models on realistic web tasks
- Developers invested in the React ecosystem who prefer open-source tooling
- Non-React or non-frontend stacks — the shipped tooling is React-specific
- Buyers who need a managed SaaS with onboarding, SSO or support contracts
- Teams that require a purchasable agent-evaluation product with a published tier list today
We scan live Reddit threads, YouTube comments, X posts, G2 reviews and other communities — and hand you an honest verdict in under a minute.
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- Real pros & cons from real users
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Skip Million if your stack isn't React — both shipped tools, React Scan and React Doctor, are React-specific, so Vue, Svelte, Angular or backend-only teams get nothing from an install.
Million's public homepage presents its shipped tooling, React Doctor and React Scan, as open-source and free, with a contact address for everything else — so there is no published tier ladder to compare against cheaper React linting setups or more expensive commercial code-quality platforms. Budget your time, not licence spend, and evaluate ReactBench as a separate decision once Million publishes how it's accessed.
In short
Million — Million open-sources React Doctor (15k stars) and React Scan (22k stars), and is building ReactBench to check AI-written React before it ships. Best for React teams wanting runtime and rendering checks beyond static lint rules, Engineering teams running AI coding agents that need code review help before merge, Agent builders evaluating coding models on realistic web tasks. Contact Sales pricing.
What people actually say about Million — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
117 mentions across 8 sources (Hacker News, YouTube, Product Hunt, App Store, Stack Overflow, GitHub, Lemmy, Tech Press) · researched Aug 28, 2026.
Average across the 8 sources that answered — each source counts once, not each post.
- +Strong founder credibility from React Scan and React Doctor projects.
- +Mission directly addresses a real pain: verifying AI-generated code.
- +Backed by Y Combinator and notable angels in the AI space.
- +Open-source ethos likely to attract community contributions.
- +ReactBench benchmark could standardize coding agent evaluation.
- −No public product, pricing, or documentation yet.
- −Homepage is just a mission statement, lacking substance.
- −GitHub issues show integration problems in related tools.
- −Uncertain if ReactDoctor/ReactScan will be merged into Million.
- −Lack of user reviews makes real-world reliability unknown.
- • No public pricing means potential for high custom costs.
- • Time investment in evaluating an unproven tool.
Viability Score
How well maintained and how widely used is Million? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- React Scan — open-source tool that detects and highlights rendering performance issues in React apps
- React Doctor — open-source utility that diagnoses issues across a React codebase
- GitHub-hosted tools with public star counts (React Scan 22k, React Doctor 15k)
- ReactBench — benchmark for evaluating coding agents on realistic web development tasks
- Custom datasets built for training and grading frontier coding agents
- Reinforcement learning environments for agent training
- Trace collection and analysis of coding agent behaviour
- Open-source inspection of AI-generated React code before it ships
- Browser-based page inspection view on the Million site
- Direct contact route for collaboration and early involvement
- Backed by Y Combinator (W24)
- Angel-backed with investors including Scott Wu, Amjad Masad, Evan You, David Cramer, Matt Biilmann, Sahil Lavingia, Theo Browne, Koen Bok
About Million
Million Software, Inc. is an early-stage company with one thesis: AI coding agents now write a lot of code, and someone has to confirm it actually works. What you can use today is open-source React tooling. React Scan (22k GitHub stars) detects and highlights rendering performance problems in React apps. React Doctor (15k stars) runs diagnostics across a React codebase and surfaces issues for you to fix. Both are free, GitHub-hosted, and aimed at React teams who want runtime and rendering checks that ESLint rules don't catch. The second half of the mission is ReactBench, a benchmark Million is building to evaluate coding agents on realistic web development work. It is paired with custom datasets, reinforcement learning environments, and trace collections, so the same assets can grade an agent or be used to train one. That half is aimed at agent builders and teams deploying coding agents, not at app developers shopping for a linter. Million is backed by Y Combinator (W24) and an angel list that includes Scott Wu, Amjad Masad, Evan You, David Cramer, Matt Biilmann, Sahil Lavingia, Theo Browne, Koen Bok and others. Evan You's involvement matters if you work in React — it signals the tooling side is not a side project. If you run React in production and AI agents open your pull requests, the scanning tools are usable now; the benchmark is a thing to watch.
Behind the Verdict
Million is really two companies sharing a roof, and it's worth separating them before you spend time on either. The first is open-source React tooling, and this part is real and shipping. React Scan (22k GitHub stars) detects and highlights rendering performance issues in React apps — the class of problem where a component re-renders more than it needs to and your frame budget quietly disappears. React Doctor (15k stars) goes wider: it diagnoses issues across a React codebase rather than watching one running app. Together they cover a gap that static lint rules handle poorly, because re-render behaviour is a runtime property, not a syntax one. Both are free and hosted on GitHub, so adoption cost is close to zero and you can read the source before you trust it in CI. The second half is ReactBench plus custom datasets, reinforcement learning environments and traces. Million's stated goal is to train and evaluate frontier coding agents on realistic web development work. That's a meaningfully different buyer: teams building or deploying coding agents, who today either write their own eval harness or lean on general-purpose benchmark suites that don't reflect a real React codebase. The pitch of one asset set that both grades and trains an agent is coherent. The catch is that nothing on the homepage tells you how to buy access, what it covers, or how results are scored. Strengths: free, inspectable tooling with genuine star traction; a team with the React-runtime instincts to make the scanners useful; a Y Combinator W24 backing and an angel list (Scott Wu, Amjad Masad, Evan You, David Cramer, Matt Biilmann, Sahil Lavingia, Theo Browne, Koen Bok) that de-risks the tooling side specifically — Evan You's presence is the signal that React tooling is the point, not a marketing detour. Weaknesses and where it doesn't fit: this is an early-stage company, and the shipped surface is developer tooling rather than a managed platform. The tooling is React-specific, so Vue, Svelte, Angular or backend-only stacks get nothing. ReactBench and the datasets are described as things Million builds, not as a product you can evaluate on a trial. If you need a vendor with a support contract, onboarding and an SLA, Million's public positioning doesn't currently offer that. Where it fits: React teams that want runtime rendering checks alongside their lint setup, and engineering teams running AI coding agents that want code inspection help before merge. Where it doesn't: anyone who needs a signed contract and a support queue today, and anyone outside the React ecosystem.
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Real-world workflow fit
Concrete scenarios for the personas Million actually fits — and what changes day-one when you adopt it.
You install React Scan from GitHub, open your running app, and it highlights components that re-render more than they should during normal interaction.
Outcome: You identify the offending components and stop a frame-rate problem before it reaches production, at zero licence cost.
Cursor or Copilot opens a pull request touching React components; you run React Doctor across the branch and pair it with React Scan on the preview build.
Outcome: Rendering and codebase issues get caught in review rather than by your users, and your reviewers get a concrete issue list instead of a vibe check.
You need to know whether a coding model can handle realistic web development tasks, not toy prompts, so you line up ReactBench alongside the custom datasets and RL environments Million describes.
Outcome: You get an evaluation approach aimed at real React work — with the caveat that you'll need to contact Million directly to understand access and coverage.
Use Cases
- Find and fix unnecessary re-renders in a React app with React Scan before they hit production.
- Run React Doctor across an existing React codebase to surface accumulated issues for triage.
- Add runtime rendering checks to your review process for pull requests authored by AI coding agents.
- Contribute to or fork the open-source React tools to fit your own repo conventions.
- Evaluate how a coding agent performs on realistic web development work using ReactBench.
- Train or fine-tune a coding agent with custom datasets and RL environments.
- Analyse traces of coding agent behaviour to understand where an agent goes wrong.
- Give a React team a free, inspectable second opinion beyond what ESLint rules catch.
Limitations
- The public homepage presents Million as an early-stage company whose shipped offerings are the open-source tools React Doctor and React Scan.
- ReactBench, the custom datasets, reinforcement learning environments and traces are described as resources Million builds to train and evaluate frontier coding agents; no product page, coverage detail or scoring methodology for them appears in the evidence.
- The tooling is React-specific, so Vue, Svelte, Angular or backend-only work is out of scope.
- No underlying AI model names appear anywhere in the provided evidence, so treat any claim about which models ReactBench evaluates as unverified.
- The homepage offers a contact address for outreach rather than a self-serve path.
as of 2026-10-05
Verification history
We have re-verified Million 9 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 9 verification passes.
Free to cite with attribution — this page re-verifies continuously.
Where the pricing makes sense
The company stage and team size where Million's pricing actually pencils out — and where peers do it cheaper.
Million's public homepage presents its shipped tooling, React Doctor and React Scan, as open-source and free, with a contact address for everything else — so there is no published tier ladder to compare against cheaper React linting setups or more expensive commercial code-quality platforms. Budget your time, not licence spend, and evaluate ReactBench as a separate decision once Million publishes how it's accessed.
Setup time & first value
How long it actually takes to get something useful out of Million — broken out by persona, not the marketing-page minute.
React developer: minutes — both React Scan and React Doctor live on GitHub, so you clone, install and have a first scan running the same session. Frontend lead adding them to CI: roughly an afternoon to wire the checks into your review workflow and tune out noise. Agent builder wanting ReactBench: not a timed install — reach out to Million first, since access and coverage aren't published on the
Switching to or from Million
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From ESLint plugins alone: keep ESLint for static rules and add React Scan for the runtime re-render problems static analysis can't see.
- →From manual React DevTools profiling: run React Scan on the running app for continuous highlighting instead of profiling each interaction by hand.
- →From ad-hoc PR review of AI-generated React code: add React Doctor to the branch so a tool lists the issues before a human reads the diff.
- ↗To a general-purpose eval suite: if you need benchmark coverage beyond realistic web development work, ReactBench alone won't cover it.
- ↗To a commercial code-quality platform: if you need onboarding, SSO and a support contract, Million's open-source tools aren't that product.
- ↗To another frontend stack's tooling: React Doctor and React Scan have no equivalent for Vue, Svelte or Angular projects.
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Million”, and we withheld 6: 6 could not be judged, because “Million” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Million.
Official links
Tools that pair well with Million
Common stack mates teams adopt alongside Million, with the specific reason each pairing earns its keep.
Stagehand
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Chrome DevTools MCP
Open-source MCP server that gives coding agents live Chrome DevTools access for debugging, automation, and performance traces.
Open Interpreter
Open Interpreter is an open-source terminal agent that turns plain-English requests into real file edits and shell commands on your machine.
Featured Head-to-Head Comparisons
Million vs Spider Cloud
Million and Spider Cloud serve entirely different needs. If your pain point is ensuring AI-generated code actually works before deployment, Million is the specialized tool—but it's unproven at scale and requires a sales conversation. If you need fast, reliable web data for AI agents or RAG, Spider Cloud is production-ready with a freemium model and clear pricing. Choose based on your primary bottleneck: code correctness vs. data ingestion.
Million vs Voyage Ai
Choose Million if you are an engineering team deploying AI-generated code and need to prove correctness before production. Choose Voyage AI if you are building enterprise RAG pipelines that demand high retrieval accuracy on domain-specific documents like finance or legal. They solve different problems: verification vs. retrieval.
Million vs Temporal Ai
Million and Temporal AI serve very different needs. If your pain point is trusting AI-generated code to be correct before merging, choose Million. If you need to build resilient, long-running AI agents that survive crashes and retries, choose Temporal. For most teams, these are complementary – use Million for verification and Temporal for orchestration.
Alternatives to Million
View allStagehand
Open-source SDK for building browser agents with AI primitives (Act, Extract, Observe, Agent) plus Playwright-style controls in TypeScript, Python, and Go.
Chrome DevTools MCP
Open-source MCP server that gives coding agents live Chrome DevTools access for debugging, automation, and performance traces.
Open Interpreter
Open Interpreter is an open-source terminal agent that turns plain-English requests into real file edits and shell commands on your machine.
Frequently Asked Questions
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