Xenaris 4.x
The intelligence factory for private M&A
What it does
Xenaris watches the private market continuously: standing Mandates sweep weekly, score sell-readiness on cited public signals, map likely buyers, and settle every call against real outcomes in an append-only ledger. Not another database - finished research.
The consent protocol for private-company M&A intelligence. Find off-market deals 3-6 months before the market.
Every week Xenaris reads the companies that matter to your mandate, from thousands of public and under-indexed data points, and keeps score on whether it was right. Every claim cites its source. No card for the first scan. Names and sources open once you are signed in. Registry filings, leadership exits, a hiring freeze nobody announced, a partner who went quiet. The signals are public and legal - just never indexed by the tools you pay for. Each one is cited to its source and scored against what actually happened next. We started Xenaris with a simple idea: a deal team should know a company is ready to sell before the banker calls - and the system that told them should be graded on whether…from xenaris.io
Does the same job
all alternatives →
Portfolio Activity Monitor by Auquan2020 · ▲74Discover news and investment insights ahead of the market
More commerce this month
the category →
Compare your startup equity grant for free.
Commerce · 26d ago · equitybee.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