MapleFlow.io - One Key for Everything
One key for AI, identity verify, and utility APIs
What it does
The Everything API for builders. Power you apps with AI models, ID Verification, and many more utility features without juggling keys or minimum spends. 34 AI models across 7 providers, plus face verification and utility APIs — all on one key, one credit balance. Verify a face for ~$0.02 instead of $1-2 from Persona/Onfido. And more features as we build together.... No seats. No enterprise sales calls. Credits don't expire.
The Everything API for builders. AI models, identity verification, and everyday tools on one key, one credit balance. Priced for indie devs and small startups, not enterprise procurement.
34 AI models, face verification, translate, weather, currency — behind one key, one credit balance. Priced for indie devs and small startups. No enterprise sales cycle. Sign in, grab a key, make your first call. No config, no cards, no waiting on a sales call. One click with Google or GitHub. Your API key is ready right after. Same API key works for AI, translation, weather, currency, verify — everything. Only pay for actual token usage. Unused tokens auto-refunded. Credits never expire. from openai import OpenAI client = OpenAI ( api_key= "sk_live_..." , base_url= "https://api.mapleflow.io/v1" # just change this ) response = client.chat.completions. create ( model=…from mapleflow.io
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Life & fun · 10d ago · louisabraham.github.io


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Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io


I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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