Vazagency
Recover damaged ratings on Trustpilot, Google & more
What it does
Vazagency helps businesses understand and recover from damaged online ratings. Use free rating calculators, review-response generators, reputation audits, practical recovery guides, and managed support across Trustpilot, Google, Yelp, and other major review platforms. Calculate what it takes to reach your target rating, respond professionally to negative feedback, and build a stronger online reputation.
Buy Trustpilot, Google, and Yelp reviews from $100 — or get a free review sample first. Vazagency recovers damaged ratings across 38 platforms, with paced delivery and 30-day replacements.
Buy real Trustpilot and Google reviews to fix a damaged rating, plus SEO that actually ranks. Checked against how Trustpilot currently ranks listings: recency and consistency still beat raw count. Recency weighting — newer reviews influence TrustScore more than older ones. Live, anonymized results from visitors who used the rating-recovery calculator on this page to plan their jump from a current rating to a target rating — last updated September 5, 2026 . All figures are aggregated and fully anonymized — no personal or account data is ever shown. A structured recovery process moves your business from an eroded, unmanaged reputation to one that actively builds customer trust. SEO gets your…from vazagency.com
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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