Alrim Labs
GTM and Positioning Studio
What it does
What sets Alrim apart is that it owns the full loop: create, ship, validate, iterate. Most competitors sell a one-time artifact and walk away. Alrim stays in the loop. And at a fraction of what US agencies charge (sub-$2,500), it makes serious GTM support accessible to non-US founders who are otherwise priced out of the market entirely.
Alrim Labs builds category-defining positioning, viral growth engines, and product psychology frameworks for B2B SaaS and high-growth AI companies. Book a 30-min strategy audit.
Does the same job
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- FOFind out if your SaaS is underpriced in 10 minutesApr 2026 · github.com · ▲7
GTM iteration is slow by nature. Test the price, wrong. Fix the message, doesn't convert. Try a new audience, wrong segment. Pick a channel, no traction. Each mistake costs a month. By the time you've iterated to something that works, the market has moved - especially now, when AI is reshaping what buyers want every quarter. We built RightSuite to compress that cycle. Describe your offer and target audience. The system runs it through a synthetic buyer population and tells you what's likely broken before you go live. It won't replace talking to real customers. Nothing does. But it means you…
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 · 17d ago · simedw.com