Opportunities › AI-assisted code review for development teams › Proposed app
Proofbench
Test AI code reviewers on your own past pull requests, then pick with evidence
- Score
- 49
- confidence 38
- Evidence
- 4
- items on the page
- Rivals
- 0
- named in sources
- First version
- 35 d
- estimate
- Type
- Desktop app
- PWA: runs in the browser, installs on Mac and Windows
- Market since
- 2023
- Emerging market · AI estimate
ScreensConcept
Desktop app: Engineering teams spend extended sessions comparing detailed pull request reviews side-by-side in dense tables and reports. Sample screens on a computer, in the proposed brand. Their numbers are sample data.
New bench
Sandbox only60 PRs
About this appAI proposal
Proofbench helps engineering teams choose and keep an AI code reviewer. Instead of running several free trials on live work, you replay a sample of your team's closed pull requests through the reviewers you are considering and compare what each one catches, misses and gets wrong.
It is built for teams of 40+ developers where code review is a regular requirement and the choice of AI review tools is hard to compare. Reviewers are scored against the comments your own people made, so results reflect your code, not a vendor demo.
After you choose, Proofbench stays as a light layer: it tracks which AI comments your team accepts or dismisses and flags when a tool gets noisy. Everything on this page is a proposal to be tested.
- Tagline
- Choose your AI code reviewer on your own code, not a demo.
- Voice
- PlainMeasuredDirect
- Why this name
- A bench is where tools are tested side by side, and proof is what teams want before buying. Two plain words joined.
In the first version
Members say which features they would use. It tells PWAS what people want; it changes no score.
Replay past pull requests
Pick 20 to 200 closed PRs and run each candidate reviewer on them in a sandbox. No live branches are touched during evaluation.
No member yet
Scores against human reviews
Compare each AI comment to what your reviewers actually said: matched, missed, extra or wrong. Results by repo and language.
No member yet
Side-by-side comment view
Read two or three reviewers' comments on the same diff line, next to the human comment and the final merged fix.
No member yet
Trial planner
Track each tool's trial dates, seats and checklist: review quality, incident response, branch management fit. One shared decision page.
No member yet
Brand identityAI proposal
Check the name against trademark registers before using it.
Palette
#1F5C4APine · primary#F6F3ECPaper · surface#1F2A24Ink · text#E07A2FEmber · accent#3C7DA6Slate blue · data
Typography
Aa
Proofbench
ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
Choose your AI code reviewer on your own code, not a demo.
PricingAI proposal
The material gives no competitor prices. These tiers are a starting point to test, built around team size, as the opportunity suggests.
Trial bench
Free
- One bench of up to 20 PRs
- Two candidate reviewers
- Shareable report
Team
$199 a month
- Unlimited benches up to 200 PRs
- Trial planner
- Acceptance tracking for 10 repos
- Up to 50 members
Org
Contact us
- Unlimited repos and members
- SSO
- Private model endpoints
- Contact us
Would you pay Team · $199 a month?
Your answer tells PWAS which prices people accept. It changes no score.
No answers yet.
What it could be worthEstimate
What a software business making this much sells for today, from real deals. Pick a monthly revenue.
If it makes
Worth about
$194,000
Sale range $132,000 to $263,000
$120,000 a year in revenue
From 87 software businesses listed and sold on Empire Flippers in the last year, revenue vetted by the broker: they sell for about 19× their monthly revenue, most between 13× and 26×.
Measured on profit, the middle deal is 32× monthly net profit: about 2.7 years of profit.
An estimate, not an offer or financial advice. A real price depends on profit, growth, churn, how much of the work is the owner's, and the buyer.
How it would growAI proposal
How the product would reach new customers through its own use, and how the first ones would be found. A plan to test, not a result.
- Built-in loop
- Shared outputs. Leads export a decision report with method and scores and send it to security, finance and other engineering groups, who see the Proofbench name and a link to run their own bench.
- Do they become customers?
- Report readers are often buyers, but may only read it once. Test whether readers at other teams or companies start their own bench from the report link.
- First customers
- Engineering managers or platform leads at software companies with 40 to 150 developers who are currently trialing at least two AI code review tools.
- Where to reach them
- Hacker News: Post a method write-up on benchmarking reviewers on your own PRs, and offer free benches to commenters in similar threads.
- Engineering leader communities: Offer a free bench to leads in Slack and forum groups for engineering managers, in exchange for feedback.
- First milestone
- Five teams of 40+ developers each complete a bench, and at least two pay for the Team tier within 60 days.
Why people already pay for this
- VerifiedHacker News post received 26 points and 31 comments
- Public claimMultiple AI-assisted code review tools exist in the market, creating evaluation challenges for teams
- Public claimDevelopment teams actively use AI-assisted code review tools for multiple purposes including code review, incident response, and branch management
- Public claimTeams of 40+ developers are evaluating and adopting AI-assisted code review solutions
Tech stack
Every proposal builds on the same PWA base, installable from the browser on any phone or computer. Dashed boxes are what this app adds.
- AppNext.js and TypeScript
- PWAManifest and service worker
- UITailwind CSS
- Data and authSupabase Postgres
- PaymentsStripe
- EmailResend
- HostingVercel
- This app · Git host integrationRead-only GitHub and GitLab appsNeeded to import closed PRs and human review comments for replay.
- This app · Job queueBackground worker queueReplays run for many minutes and fan out across reviewers.
RisksAI inference
- TechnicalEach AI review tool exposes different ways to run on a past PR. Some may need a live repo or app install, which limits which reviewers can be benchmarked.
- DataTeams must trust a new vendor with private source code. Security review could slow sales to larger teams.
- CommercialEvaluation is a one-off need. Retention depends on post-adoption tracking being valuable enough to keep paying.
- AIMatching AI comments to human comments is itself judged by a model and can be wrong, which could undermine trust in scores.
- PlatformReview tool vendors may block benchmarking or change terms, and could ship their own comparison features.
Everything marked AI proposal or AI inference was written by a model from the evidence on the opportunity page. The proposed name must be checked against trademark registers before it is used.