Figr 2.0

In plain words

Figr 2.0 is a design resource platform that lets users browse and copy editable user interfaces from popular apps directly into Figma. Rather than static screenshots, the designs are fully editable, allowing designers to customize and adapt them for their own projects. The platform offers tailored recommendations to help users discover inspiration across different applications, making it useful for designers seeking real-world UI examples and design patterns.

written from the facts on this page · September 2026

From the sources

Design like a pro with figr.design! More than just screenshots. Each design you see on Figr can be copied to Figma and edited any way you want. Browse through popular apps and get tailored recommendations to find the best inspiration.

• 
  Clipto MCP▲640

  Let agents source clips from terabytes of your local video

  Work · 18d ago · clipto.com

• 
  HyNote for Mac▲383

  Free local transcription that is 100% Private

  Work · 17d ago · hynote.ai

• 
  VoiceOS App Store▲330

  The app store for voice native apps that lives in your notch

  Work · 28d ago · voiceos.com

• 
  Scrimba Explain▲325

  Ask any question, get a video back instantly

  Work · 24d ago · scrimba.com

• 
  The New Calendly▲211

  Handle all of the work before, during, and after meetings

  Work · 17d ago · calendly.com

• 
  Resend▲1,326

  Email for developers

  Dev tools · 2023 · resend.com

• 
  STORI AI▲1,320

  Your ideas become visually compelling branded social posts

  AI · 2023 · storiai.com

• 
  Kombai▲1,080

  A new AI model that you can prompt with UI designs

  AI · 2023 · kombai.com

• 
  User Persona Generator▲1,014

  Understand your audience without 50 interviews

  AI · 2023 · founderpal.ai

• 
  Lottielab▲871

  Create and ship lottie animations to sites and apps faster

  Dev tools · 2023 · lottielab.com

• LC
  LLMs can generate valid JSON 100% of the time▲854

  Outlines is a Python library that focuses on text generation with large language models. Brandon and I are not LLM experts and started the project a few months ago because we wanted to understand better how the generation process works. Our original background is probabilistic, relational and symbolic programming. Recently we came up with a fast way to generate text that matches a regex (https://blog.normalcomputing.ai/posts/2023-07-27-regex-guide...). The basic idea is simple: regular expressions have an equivalent Deterministic-Finite Automaton (DFA) representation. We…

  AI · 2023 · github.com