Merge PRs 8× Faster with confidence

For tech teams that want to ship waaay faster with AI and confidence

Connect your AI assistant to Preveo through MCP to evaluate UI, compare changes, and investigate performance. Give your team shared evidence to guide fixes and review what ships.

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FROM CODE CHANGE TO TEAM REVIEW

From a code change to a review you can trust.

See how a frontend change becomes a pull request with evidence your team can review.

HOW IT WORKS IN UNDER 30 SECONDS

STEP 1 OF 3

Alex changes the pricing page

Alex · Developer“Add new pricing plan Team in the middle of the bundles”
Pricing pageFrontend
Find the right plan
Starter
Team
Business
Team plan added between Starter and Business

AI build websites,
Preveo evaluates them

THE PR REVIEW DIFFERENCE

More confidence. Less time in review.

AI coding assistant using Preveo gives reviewers visual changes and check results, and alerts the right expert when something breaks.

Reach review-ready confidence with Preveo

Reviewer confidence over PR review timeAn illustrative two-axis graph. With Preveo, reviewer confidence reaches the review-ready level at 3 minutes. Without Preveo, reviewer confidence remains below the review-ready level at 30 minutes.Review-readyGrowingLow010203040PR review time (minutes)Reviewer confidence3 min · With PreveoSame confidence not reached after 30 min - without Preveo

Scroll to see the full graph →

BUILD. EVALUATE. IMPROVE.

AI build websites.
Preveo evaluates them.

From your agent harness to your team’s review, bring the evidence into every decision.

Evaluate your localhost changes before you publish

Connect through MCP to automatically create a temporary Cloudflare tunnel, so Preveo can evaluate your localhost changes as you build, before you publish.

Connect your agent harness
Example page evaluation report

Bring in the right reviewers when your agent needs help

Keep your team focused while the agent works. When it needs a human decision, notify only the relevant reviewers and give them the evidence they need to help.

  • Relevant reviewers only
  • Notifications when help is needed
  • Evidence for informed decisions
Example report: Would ChatGPT recommend this page?

Bring your repository team into Preveo

Ask your connected agent to onboard contributors from your Git repository. It can find available email addresses and send project invitations with the access level you choose.

  • Invite repository contributors
  • Choose their project access
  • Review invitation results
Connect your agent
AN EXAMPLE REQUEST
“Invite this repository's contributors to my Preveo project as engineers.”
  1. Find your teamThe agent checks available repository contributor information.
  2. Send invitationsPreveo emails the identified recipients with your chosen access.
  3. Share the projectTeammates get access after they accept their invitations.

Catch what your desktop preview hides

Review your page across screen sizes, browsers, themes, and languages. See where the experience breaks before your users do.

  • Responsiveness
  • Desktop vs Mobile
  • Cross Browsers
  • Light vs Dark
  • RTL vs LTR
  • Localization
  • + More
Example responsive layout review

Catch issues introduced by your changes

Automatically capture performance metrics, console errors, and failed requests as you review changes. Add focused macros to help explain the evidence and guide your next fix.

  • Page Performance
  • Core Web Vitals
  • Console Errors
  • Network Errors
Preveo page performance statistics

Did the build match the design?

Compare your implementation with the intended design, or put before and after side by side. Review the spacing, typography, and layout that make the difference.

  • Design vs implementation
  • Before vs after
  • Treatment A vs B
Example design and implementation review

Find bugs together, on your own time

Invite teammates and clients to review a feature when it suits them. Keep their notes, bugs, and questions together in a shared thread for follow-up.

Get the browser extension

Share the evidence behind your next release

Bring screenshots, recordings, comparisons, and reports together in project threads. Give teammates and clients the context to review what changed.

  • Shared evidence
  • Project threads
  • Reusable macros
Create a shareable review
Preveo product preview with sharing controls

Keep everyone in the loop on project progress

Give clients and non-technical stakeholders a clear view of project progress. Explore shared work and review changes at your own pace.

  • Project overview
  • Shared work
  • Review at your own pace
Explore your projects

Give your agent harness the evidence to evaluate what it builds

Connect through MCP to run evaluations, inspect screenshots and reports, and use findings to guide fixes and validate changes.

Connect your agent harness Browser sign-in. No API key to copy.
AN EXAMPLE REVIEW
“Check this pricing page on mobile and help me fix the issues.”
  1. Run a focused evaluationThe harness selects the page, devices, and checks.
  2. Inspect the evidencePreveo returns captures and saved macro findings.
  3. Fix, then review againThe harness uses the findings to guide the next change.
Explore the MCP tools

Macros

Not Skills, but Macros: Evaluations Everyone Can See and Understand

A macro evaluates your page and shows you what to improve. Choose a ready-made check for SEO, layout, copy, and more, or create your own.

See how clearly your page explains what you offer, and what could help AI assistants recommend it.

Try this macro

Will ChatGPT Recommend This Page?

How it works

Get started in three steps

Review your website with the browser extension or connect your AI assistant through MCP.

  1. 1

    Add Preveo to your agent

    Follow your agent's MCP setup instructions. For example, with the Codex CLI installed, run:

    Terminal
    codex mcp add preveo --url https://api.preveo.io/mcp
codex mcp login preveo
  2. 2

    Sign in and approve

    Follow your agent's sign-in flow, then create a Preveo account or sign in and approve the connection.

    You can disconnect anytime in Preveo under Connected apps.

  3. 3

    Start working

    Open a new conversation with your agent and try:

    Use Preveo to list my projects.

    Or ask: “Push my changes and create PR”

Why Preveo?

Building is only half the job.

What happens after AI says "Done"? Your builder helps you create the product. Preveo helps you judge whether it is ready to ship.

Keep the builder you love. Add a dedicated evaluation layer.

Scroll to compare
How Preveo compares with AI builders and coding agents, from our perspective.
Building is only
half the job.
What happens after AI says "Done"?
PreveoEvaluation layer
LovableLovableBuilder / agent
ReplitReplitBuilder / agent
BoltBoltBuilder / agent
Claude CodeClaude CodeBuilder / agent
OpenAI CodexCodexBuilder / agent
CursorCursorComposer 2.5 Fast
v0v0Builder / agent
Building and independent evaluation
Primary jobEvaluate your productBuild your appBuild your appBuild your appBuild & fix codeBuild & fix codeBuild & fix codeBuild your app
Generate code
Suggest fixes to your code
Can client/teammate evaluate the builder's work ?
Need source code for a page reviewNot requiredProject-based workflowProject-based workflowProject-based workflowOptional with browser toolsOptional with browser toolsOptional with browser toolsProject-based workflow
Repeatable quality, clear evidence, and client handoffReady-made checks for UX, SEO, AI discoverability, accessibility, responsiveness, and content. Choose the evaluations that matter to your product.
Know what to checkReady-made evaluationsTesting tools + promptsApp testing + promptsPrompts / project toolsSkills / custom setupSkills / custom setupRules / custom setupProject tools + prompts
Use the same quality standard everywhereReusable macro criteriaSaved instructions / promptsSkills / custom setupSaved prompts / setupSkills / custom setupSkills / custom setupRules / custom setupSaved instructions / prompts
Find problems you didn't know to ask about
Run the exact review againRe-run saved macros
Compare before vs after
Show evidence, not just explanations
Understand results without being technicalVisual, plain-language reports
Prove quality to a clientShareable evaluation findings
Discuss findings together
Share a review document
Invite clients and teammates
Estimated review costs
Usage pricing basisShared credit walletCredits per message / workEffort-based usageMonthly token allocationSubscription or API tokensSubscription or API tokensModel-based token usageUsage credits
Responsive layouts~2.3–3.9×~50–150×~25–200×~5.1–26.8×~6.1–27.2×~6.1–27.2×~9.2–40.8×~6.1–27.2×
SEO~0.16–0.27×~12.5–37.5×~6–50×~1.8–5.3×~2.4–6.6×~2.4–6.6×~3.6–9.9×~2.4–6.6×
AI search / AEO~0.24–0.39×~25–75×~12–75×~2.5–7.3×~3.6–9×~3.6–9×~5.4–13.5×~3.6–9×
UX and conversion~1.4–2.4×~25–100×~12–100×~2.8–14×~3.8–16×~3.8–16×~5.7–24×~3.8–16×
Accessibility~1.7–2.8×~25–100×~12–125×~3.5–16.5×~4.4–18×~4.4–18×~6.6–27×~4.4–18×
Content and grammar~0.24–0.36×~12.5–25×~6–25×~2.5–5×~3.6–7.2×~3.6–7.2×~5.4–10.8×~3.6–7.2×
RTL and localization~2–3.3×~37.5–125×~25–150×~4.1–21.8×~5.3–23×~5.3–23×~8–34.5×~5.3–23×

Built to work together. Use Preveo to find and understand the issues, then take the findings back to your builder to fix them.

AI cost assumptions and sources

Each range uses the same small-run AI cost reference. Larger checks can cost more for Preveo too. Estimates describe processing usage, not customer prices or measured savings.

Cost colors use the range midpoint: green: low (up to 5×), yellow: medium (above 5× to 20×), red: high (above 20×).

These estimates combine the macro runtime structure with assumed token budgets for each review. The code batches captured views into one processing request, uses a text or vision model according to the evidence, and renders a saved report template. The token budgets below are engineering assumptions, not measurements or fixed macro definitions.

  • Responsive layouts. One page, six screen sizes.
    Preveo budget: 18k in / 2.5k out → 30k in / 4.5k out.
    Agent budget: 18k in / 2.5k out → 100k in / 7.2k out.
    Lovable: 2–6 assumed credits. Replit: ~25–200× assumed paid usage.
  • SEO. One page, metadata and DOM evidence; no images.
    Preveo budget: 6k in / 1.2k out → 10k in / 2k out.
    Agent budget: 6k in / 1.2k out → 18k in / 3k out.
    Lovable: 0.5–1.5 assumed credits. Replit: ~6–50× assumed paid usage.
  • AI search / AEO. One page, content and structured data; no external research.
    Preveo budget: 8k in / 2k out → 14k in / 3k out.
    Agent budget: 8k in / 2k out → 25k in / 4k out.
    Lovable: 1–3 assumed credits. Replit: ~12–75× assumed paid usage.
  • UX and conversion. One page, three captured states.
    Preveo budget: 9k in / 2k out → 15k in / 3.5k out.
    Agent budget: 9k in / 2k out → 50k in / 6k out.
    Lovable: 1–4 assumed credits. Replit: ~12–100× assumed paid usage.
  • Accessibility. One page, two captures plus DOM audit evidence.
    Preveo budget: 12k in / 2k out → 20k in / 3.5k out.
    Agent budget: 12k in / 2k out → 60k in / 6k out.
    Lovable: 1–4 assumed credits. Replit: ~12–125× assumed paid usage.
  • Content and grammar. One page of text, one language; no images.
    Preveo budget: 8k in / 2k out → 12k in / 3k out.
    Agent budget: 8k in / 2k out → 16k in / 4k out.
    Lovable: 0.5–1 assumed credits. Replit: ~6–25× assumed paid usage.
  • RTL and localization. Two directions at two screen sizes, four captures.
    Preveo budget: 14k in / 2.5k out → 24k in / 4k out.
    Agent budget: 14k in / 2.5k out → 80k in / 7k out.
    Lovable: 1.5–5 assumed credits. Replit: ~25–150× assumed paid usage.

The lower agent budget assumes a batched review. The upper budget assumes sequential evidence collection and analysis with repeated context; this is a scenario, not a claim about how every product operates. Image input is included as estimated token-equivalent evidence. Actual image charges and token counts differ by provider and tokenizer.

Preveo estimates use the repository defaults: DeepSeek V4.1 Flash for text and Gemini 3.8 Flash for images. Deployment settings and routing can change the model and price. Compilation and report-template creation are excluded because the estimate is for running an existing macro.

Claude Code estimates use Sonnet 5.5 API rates; Codex uses GPT-6.1 Sol Standard API rates; Cursor uses the higher-cost Composer 2.5 Fast scenario at $3 per million input tokens and $15 per million output tokens. Standard Composer 2.5 costs less ($0.50 input / $2.50 output per million tokens). These selected models do not represent every available model or subscription. Bolt uses the monthly Pro token-allocation equivalent, including the plan price spread across its allowance, rather than an incremental bill. These billing bases differ, so the table is not a comparison of actual customer spending.

Lovable estimates allocate the monthly Pro plan across its included credits and use the assumed per-review credit budgets above. The published examples cover small edits and app creation, not these audits; our review budgets are extrapolations. Chat-only reviews can cost less, and allowances can cover usage.

Replit estimates use assumed paid-request budgets informed by its July 2025 pricing recap, which described inexpensive simple requests and higher charges for involved work. Those historical examples are not a current price list or measured review costs. Current billing documentation confirms effort-based paid usage and Free Mode allowances. These ranges are scenarios, not guaranteed minimums or maximums.

v0 estimates use the published v0 Pro input and output rates with the same per-review agent budgets shown above. These estimate credit consumption before free allowances; they are not measured review bills. Other v0 options can cost less or more, and monthly or daily included credits can cover the usage.

All estimates exclude caching, cache writes, extra reasoning, validation retries, browser runtime, storage, hosting, provider fees, and taxes. Subscriptions and free allowances affect actual bills. Pricing checked October 5, 2026.

About this comparison

The workflow descriptions are our interpretation of the linked documentation. Builders and coding agents can also review rendered pages, collect evidence, and reuse instructions. Preveo makes independent product evaluation a dedicated workflow.

Re-running the exact review means reusing the same macro instructions and criteria, not guaranteeing identical AI findings. Before/after means re-evaluating the changed page and comparing findings. Launch-readiness checks help you assess the selected criteria.

This is our view of typical workflows, not a benchmark. “On request” means you direct the review; “with tools” and “custom setup” depend on integrations and configuration. Macros provide reusable review instructions; AI findings can vary between runs. Features vary by plan and change over time.

For “Discuss findings together,” a check means built-in comments or a shared chat. A cross means discussion needs a custom workflow or external tools. Hover over each mark for details.

For “Share a review document,” a check means a built-in shareable review report. A cross means generating a custom report or sharing a project/chat instead. Hover over each mark for details.

Explore the official product documentation:

Pricing

Start free. Top up as you go.

Create a free account, then buy credits when you need them. One-time packs. No monthly subscription.

One-time credit packs

$9one-time

Freelancer Pack · 4,000 credits

  • Builder Pack$20 · 18,000 credits
  • Product Team Pack$49 · 60,000 credits

All pack prices exclude tax.

Create free account

Explore for free. Buy credits when you’re ready.

One wallet for your workflow

  • Check your pages across different devices
  • Run ready-made macros for focused reviews
  • Review SEO, accessibility, content, and UX
  • Build custom macros for your workflow
  • Share findings with clients and teammates
  • Use a shared credit wallet in your workspace

Credits cover plugins, video captures, and storage. Larger packs give you more credits per dollar. See how credits are used.

FAQ

Frequently asked questions

Anything else? Email us at support@preveo.io.

What is Preveo?

Preveo helps you review your website, spot issues, and understand what to fix. Check your pages across devices, run focused reviews, and share findings with your team or clients.

How do I get started?

Create a free account, open your website with the Preveo browser extension, and choose the macros you want to run. Review the findings and use the suggested next steps to improve your page.

What is a macro?

A macro is a focused check for your page, such as an SEO, accessibility, content, or UX review. Start with a ready-made macro, run a few together, or build a custom one for your workflow.

Can I check a website built with AI?

Yes. Preveo reviews the website you have built, whether you used an AI builder or wrote the code yourself. Your website stays where it is; Preveo works on top of the page to help you find issues before they reach production.

Can I use Preveo on localhost?

Yes. The Preveo browser extension lets you capture directly from localhost, so you can review a page while you are developing it, before publishing it.

Can I create an account before paying?

Yes. You can create a free account, explore the dashboard, browse public crafts, and understand the workflow before you buy a credit bundle.

Do I have to subscribe monthly?

No. Preveo uses one-time credit bundles, so you only top up when your workspace needs more credits.

What are credits used for?

Credits cover paid usage such as plugins, video captures, runtime, and storage. Buy a one-time credit pack when you need more. Larger packs give you more credits per dollar, and the pricing page explains how credits are used.

Can multiple teammates share one bundle?

Yes. Credits belong to the workspace, so invited teammates can use them according to their access.

Your next step

Make your next launch stronger.

Start free with Preveo. Preview your page, find what needs fixing, and present work you can stand behind.

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