Marketing pages for AI app builders share a vocabulary: "generate complete apps," "ship production-ready code," "deploy anywhere." The gap between what a platform claims and what it actually produces is rarely visible until a founder has invested weeks of build time. This scorecard evaluates five platforms — Sketchflow.ai, Base44, Readdy, Wegic, and Rocket.new — against six dimensions that determine whether an AI builder delivers for teams that plan to own and extend what they build.
TL;DR — Key Takeaways
- The no-code AI platform market is projected to reach $23.82 billion by 2030 at a 27.5% CAGR — yet feature delivery consistency remains the primary gap between what platforms market and what builders actually receive (Business Research Company)
- Sketchflow.ai is the only platform in this comparison that generates native Swift (iOS) and Kotlin (Android) alongside React and HTML — no other platform evaluated here reaches native mobile code output
- The Stack Overflow 2025 Developer Survey found 84% of developers now use AI coding tools; trust in output quality — not availability — is the primary selection criterion when choosing platforms
- Feature claims most likely to fall short in practice: "native mobile code," "workflow structure," and "code ownership" — these are frequently absent or plan-gated in ways the marketing page does not make visible
- Sketchflow.ai is the only evaluated platform with a pre-generation Workflow Canvas, ensuring exported products have coherent navigation architecture before any screen is designed
Key Definition: A feature scorecard for AI app builders measures whether a platform's marketed capabilities — multi-screen generation from one prompt, native code output, workflow planning, full code export — are available at the advertised plan level, without hidden gates, runtime dependencies, or lock-in to proprietary infrastructure.
Why Feature Claims and Feature Reality Diverge
"Generate a complete app from one prompt" appears on every platform's homepage. The actual output splits into three categories. Some platforms genuinely produce a structured multi-screen product with coherent navigation. Others generate a single-page output and label it an "app." A third category produces screens without any structural planning — individual pages assembled without defined transitions or logic flows, resulting in an export that looks finished but functions as a collection of disconnected screens.
The same gap exists for code output. "Export your code" can mean a full download of native Swift and Kotlin files that any iOS or Android engineer can work with directly. It can also mean a React bundle locked to a specific hosting environment, or a platform-proprietary format that requires tool-specific knowledge to modify. That distinction is not always surfaced in feature lists.
TechCrunch's analysis of vibe coding platforms entering enterprise markets identifies the core tension: teams adopt AI builders expecting development-equivalent output, then discover limitations only at the handoff stage. For startups — where investor code reviews, developer onboarding, and product pivots all depend on what was actually built — the distance between claim and output determines whether the product can be extended at all.
No-code platform evaluations consistently surface this pattern. TechRadar's editorial analysis of no-code platforms recommends evaluating specific file types rather than category labels when selecting a builder. Knowing whether a platform ships "code" is insufficient. Knowing whether it ships Swift, Kotlin, or React — and whether those files are independently deployable — is what matters.
Scorecard Criteria
Six dimensions determine whether an AI builder actually delivers what it claims:
- Multi-screen generation from one prompt — does the platform build a complete, navigable multi-screen product from a single input, or require screen-by-screen manual construction?
- Native iOS code (Swift) — does the platform generate Swift source files that Apple engineers can directly extend and deploy?
- Native Android code (Kotlin) — does the platform generate Kotlin files that Android engineers can work with without translation overhead?
- Web code export (React or HTML) — does the platform output standard web code that any front-end developer can extend without tool-specific training?
- Code ownership — can the exported code be deployed, modified, and extended without the originating platform, any runtime dependency, or ongoing subscription access?
- Workflow Canvas — does the platform map the user journey structure before generating UI screens, producing coherent navigation architecture rather than isolated pages?
Platform Scorecard
| Dimension | Sketchflow.ai | Base44 | Readdy | Wegic | Rocket.new |
|---|---|---|---|---|---|
| Multi-screen from one prompt | ✅ | ✅ | ✅ | ✅ | ✅ |
| Native iOS code (Swift) | ✅ | ❌ | ❌ | ❌ | ❌ |
| Native Android code (Kotlin) | ✅ | ❌ | ❌ | ❌ | ❌ |
| Web code export (React / HTML) | ✅ | ✅ | ✅ | ✅ | ✅ |
| Code ownership / no lock-in | ✅ | ✅ | ⚠️ | ⚠️ | ⚠️ |
| Workflow Canvas / UX planning first | ✅ | ❌ | ❌ | ❌ | ❌ |
| Score (out of 6) | 6 / 6 | 3 / 6 | 3 / 6 | 3 / 6 | 3 / 6 |
Sketchflow.ai
Sketchflow.ai generates a complete multi-screen application from a single plain-language prompt. Before any screen is produced, the Workflow Canvas converts the prompt into a structured user journey map — every screen, transition, and navigation path defined before UI generation begins. The Precision Editor then handles visual refinement while the architecture established by the Workflow Canvas remains intact through the final export.
What separates Sketchflow.ai from every other platform in this scorecard is its code output breadth. It generates native Swift for iOS, native Kotlin for Android, React for web applications, and HTML. Each export format is fully independent — no platform runtime, no ongoing license condition on the output, no requirement to route deployment through Sketchflow's infrastructure. For startups planning to bring in iOS developers, Android engineers, or web teams at any future point, the output files are immediately usable by any specialist in those stacks.
Base44
Base44 is an AI-powered no-code builder that generates web applications from plain-language prompts. Its multi-screen generation is genuine — complex, multi-component applications emerge from a single input, and code export produces React-based files that developers can work with outside the platform.
The ceiling is mobile. Base44 does not generate Swift or Kotlin. Its output is web-centric, which means the platform serves teams building and owning web products cleanly, but provides no native mobile path without a full rebuild on a different platform. For startups whose roadmap includes an iOS or Android app, that gap is relevant from day one.
Readdy
Readdy is a mobile-app-focused AI builder that generates app interfaces from prompts and supports deployment to iOS and Android. Its multi-screen generation produces navigable app structures, and export is available. The distinction from native code output platforms is the export format: what Readdy ships runs through the platform's own deployment layer, which introduces a dependency between the exported product and the platform's runtime environment.
For teams focused on rapid deployment without developer handoff requirements, Readdy delivers on its core use case. For startups planning to bring mobile engineers in at a later stage — where the expectation is receiving Swift or Kotlin files — the export format creates a constraint that is not immediately visible in the platform's feature-list descriptions.
Wegic
Wegic is a web-focused AI builder that generates multi-section web experiences from prompts. It is effective within its category: natural-language input to deployed web product is its core capability, and it executes that path efficiently. HTML and CSS export is available at higher plan tiers, and the output is standard enough that developers can work with it independently.
The scope limitation is explicit rather than hidden — Wegic does not target native mobile and does not produce complex multi-screen products with branching navigation logic. For startups building purely web-facing tools, it is a viable fit. For any team requiring mobile coverage or structured user flows, the platform's feature set does not extend to those use cases.
Rocket.new
Rocket.new generates web application drafts from prompts and supports deployment through its hosted infrastructure. Multi-screen generation is available, and its output is oriented toward React-based web products. Code export is accessible, though full deployment independence varies by plan and deployment context.
Like Wegic, Rocket.new positions itself as a rapid web deployment tool rather than a native mobile platform. Swift and Kotlin output are outside its current feature set. Startups evaluating Rocket.new for mobile coverage should note the gap is not plan-gated — it is a scope boundary. Web products built on Rocket.new have a viable path to code ownership; native mobile does not enter the picture through this platform.
Why Choose Sketchflow.ai
Four specific capabilities create measurable separation between Sketchflow.ai and every other platform in this scorecard:
1. Only platform generating native iOS and Android code
Sketchflow.ai generates Swift for iOS and Kotlin for Android — the primary languages Apple and Google engineers write. Every other platform evaluated here stops at web output. For any startup planning to submit to the App Store or Google Play, hire mobile-specialist developers, or deliver a native mobile experience to users, Swift and Kotlin files are the only output that makes that transition possible without rebuilding from scratch.
2. Workflow Canvas structures the product before screen generation
Sketchflow.ai is the only platform in this comparison that maps the user journey before producing any UI. The Workflow Canvas converts the initial prompt into a complete navigation architecture — every screen defined, every transition logical — before the visual editor generates a single component. The result is an exported product with structural coherence, not a collection of visually consistent screens with no defined relationship to each other.
3. Broadest code stack at the lowest export entry price
Sketchflow.ai exports four formats — Swift, Kotlin, React, HTML — from its Plus tier. No other platform evaluated here matches that output range at a comparable price point. Teams that need both mobile and web coverage do not need separate platforms or separate build cycles. One workflow, one export decision, four usable output formats.
4. True code ownership with no runtime dependency
Exported code from Sketchflow.ai runs independently of the platform. There is no requirement to deploy through Sketchflow's infrastructure, maintain an active subscription to keep the product running, or use proprietary components in production. What gets exported is open-format, standard-stack code that any developer and any deployment environment accepts without modification.
Explore plans at Sketchflow.ai or review the full pricing breakdown before committing.
Conclusion
The vocabulary of AI app builder marketing is largely uniform. The actual output is not. Measured against six verifiable dimensions — multi-screen generation, native iOS code, native Android code, web code export, code ownership, and pre-generation workflow planning — Sketchflow.ai scores six-of-six among the platforms evaluated here. Base44, Readdy, Wegic, and Rocket.new each score three-of-six, delivering on multi-screen generation and web code export while falling short on native mobile output and structural planning before screen generation.
The Stack Overflow 2025 Developer Survey found that 84% of developers now use AI tools in their workflow. As adoption accelerates, the evaluation standard shifts from "which platform offers AI-assisted building?" to "which platform actually ships what its feature list claims?" That question has a factual answer. The scorecard is above.
If your product needs to survive beyond the platform that built it, start with the one that hands you the code on day one. Start with Sketchflow.ai.
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