Frame Decisions
Structure a high-stakes decision. Pressure test it. Decide.
What it does
Frame Decisions helps teams structure high-stakes business decisions before budget, people, vendors or technology are committed. It clarifies the decision, exposes assumptions and readiness gaps, compares realistic paths, and builds a leadership-ready Business Case Brief. Informed by industry-leading strategy and analytics frameworks, it helps you make the call with greater confidence.
Frame Decisions structures high-stakes AI, analytics and technology decisions into leadership-ready Business Case Briefs before resources are committed.
Structure high-stakes decisions into leadership-ready Business Case Briefs before resources are committed. Frame Decisions is a decision quality platform that structures high-stakes AI, analytics, product, vendor, or strategy decisions into leadership-ready Business Case Briefs — with options, risks, KPIs, readiness gaps, and a recommended path. Book a decision framing call, explore fractional analytics advisory, or bring Frame Decisions into executive learning programs. Includes AI readiness, analytics readiness, ML readiness, stakeholder alignment, and KPIfrom framedecisions.com
Does the same job
all alternatives →More growth this month
the category →
AstraPixels▲267A pixel-art solar system at its real current positions.
Growth · 29d ago · astrapixels.com

Launched alongside, August 2026
the whole month →- TL
Life & fun · 10d ago · louisabraham.github.io


- SA
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.
AI · 16d ago · simedw.com