AEONUM

AEONUM

AI for your metabolism, hormones & aging

About

AEONUM is the only platform that connects your metabolism, hormones, body composition, nutrition and habits into one answer: your real biological age. AI body analysis from photos (Gemini multimodal) — clinical-grade composition report + personalized action plan. Complete metabolic engine: BMR, TDEE, caloric periodization, 10-section clinical analysis. 6 chronobiology windows (insulin, cortisol, melatonin, autophagy, temperature, digestion) with 24h digestive heatmap and AI smart fasting. Nutrition logging with microbiome scoring and AI menu generation. 5 habit blocks × 4 levels (basic to biohacker) with pentagon radar 20 AI analyses. Solo dev from Spain. No VC

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Tastemaker
Tastemaker
Gone streaking
Gone streaking
Gone streaking 5
Gone streaking 5

Forums

Here's why I built Nebils, why actually it matters — AI Social Network For Humans, Agents, & Models

Six days ago, I launched Nebils, an AI social network where humans, agents, and models hang out together. Today, it has 117 humans and 11 agents. Nebils got #32 rank on product hunt as a product of the day (Without any paid upvotes or approaching someone, every upvote is organic ). In fact, I have never even used product hunt before this launch.
Nebils is a forkable, multi-model AI social network where humans, agents, and models evolve conversations together.
Here humans and agents both are independent users

  • Humans and Agents interact with Models

  • Humans and Agents interact with each other

  • Chat with 120+ AI models

  • Send your agents (verify within Nebils), let them interact with models, humans, and other agents

  • Publish conversations in a public feed and build your community

In Oct 2025, I was exploring karpathy's posts on X and i came across a post by him where he said that He uses all the major models all the time, switching between them frequently. One reason is simple curiosity, like he wants to see how each model handles the same problem differently. But the bigger reason is that many real world problems behave like "NP-complete" problems in these models. Here NP-complete analogy is generating a good/correct solution is extremely hard (like finding the perfect answer from scratch) but verifying whether a given solution is good or correct is much easier. He said that because of this asymmetry, the smartest way to get the best result isn't to rely on just one model, it's to:

  • Ask multiple models the same question.

  • Look at all their answers.

  • Have them review/critique each other or reach a consensus.

The AI feature your users actually want is not the one you think

Every AI product I see launching right now is racing to add the most impressive, most complex AI feature they can build. Autonomous agents. Multi-step reasoning. Real-time analysis of everything.

When we started building Murror, we fell into the same trap. We wanted to build the smartest emotional AI possible. Something that could analyze patterns across months of conversations, predict emotional states, generate deep psychological insights.

What health metrics matter most to you?

We're building AEONUM an AI-powered longevity platform that connects nutrition, sleep, exercise, stress and body

composition into one score.

Before launch, we'd love to know: what health data do you actually care about tracking?

- Sleep quality?

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