Design and diagrams decision
Sleek
A small team or single competent developer can reproduce a usable core (prompt→screens→exports) in ~1 week using existing LLMs and the Figma API, but matching Sleek's template breadth, polish, agent integrations, and billing/credit system requires more work.
Visit website↗No open-source build does this yet
Nothing published replaces this one, so a replacement starts from an empty file. Here is what it would have to cover.
What a replacement has to do
- Accept a text prompt + optional reference image → call an LLM to produce a structured screen spec → render editable screen previews in-browser → export screens as Figma layers or HTML/React with Tailwind.
What it still won’t have
- Extensive curated template/reference library and polished design presets
- Commercial-grade export fidelity and QA across many UI patterns
- Official agent skill integrations and turnkey agent setup
- Priority support, team collaboration UI, and per-seat billing UX
- Refined credit-consumption tuning and billing flows
What remains hard
- Product polish and ongoing maintenance
First-year cost
Keep paying
Paying is—cheaper in year one.
On cash alone, building overtakes the subscription at 5 seats.
Money you would actually spend
Time you would spend
—
What you would spend
What we assumed
The verdict above measures whether you could build it. This one is only about money.
Runnable build prompt
Build a minimal self-hosted AI mobile-app designer using Node.js (Express) + React frontend + Postgres. In scope: accept a text prompt and optional reference image, call an LLM (configurable, e.g., OpenAI or Anthropic) to return structured screen JSON, render editable screen previews in React, store projects in Postgres, provide REST endpoints to generate and export results, and implement exports to (a) HTML/React with Tailwind and (b) Figma via the Figma REST API. Out of scope: building a large template marketplace, multi-seat billing, and advanced design-studio features. Include input validation, error handling, unit tests for backend endpoints, and CI config for deployment. Document environment variables and a one-command local run script.
How we checked
How the score was reached
- Partly verdict base52
- 2 cited sources+1
- 3/3 assessment runs agreed+4
- Evidence score57
The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.
How scoring works →Cited sources · 2
Every page the run actually retrieved.
- official productSleek — AI Mobile App Designer | Sleek
- official pricingSleek Pricing: AI Mobile App Design Plans | Sleek
Integrity checks
What held up, and what did not.
