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About

We build biohacking that the studies actually back.

Biohacking AI is the evidence-based biohacking platform. Every claim is backed by curated PubMed primary sources — no hallucinations, no affiliate bias, no hype.

Mission

End the influencer guesswork. Start with studies.

Most biohacking content online is anecdotal, affiliate-driven, or simply wrong. A generic AI doesn't fix this: ChatGPT hallucinates PMIDs, Perplexity collapses meta-analyses into single studies. We built Biohacking AI because no platform existed that reliably separates real evidence from hype.

Our goal: Every question you have about supplements, methods, sleep, hormones, or performance should get answered with a clickable PubMed source and an honest evidence-level rating. When the data is thin, we say so. When something works in mice but is unproven in humans, we say so.

Methodology

How we weigh evidence

We follow a strict evidence hierarchy. Lower tiers are clearly labeled — never repackaged as „study".

  1. 01

    Meta-analyses & systematic reviews

    Multiple RCTs pooled — strongest evidence. We anchor every major claim here when available.

  2. 02

    Randomized Controlled Trials (RCTs)

    Single high-quality RCTs with n>50 in humans, ideally double-blind, peer-reviewed.

  3. 03

    Observational / cohort studies

    Useful for direction, but never sufficient on their own. Always labeled as such.

  4. 04

    Animal / mechanism studies

    Hypothesis-generating only. We mention them when they motivate a human trial, but never extrapolate to human dosing.

  5. 05

    Anecdote / case report

    Excluded unless explicitly framed as „n=1 experience report" in a separate section.

Editorial standards

How we publish

  • Every quantitative claim cites a specific PMID (PubMed ID) or DOI. No claim, no source — we cut the claim.
  • Effect sizes are quantified („+8% strength gain", „2.3-fold reduction"), never collapsed to „it works".
  • Dosages stay within documented safety windows. Safety notes, contraindications and interactions are surfaced inline.
  • No affiliate recommendations. No „use code SAVE10". Substance recommendations are research-driven, not commercial.
  • Every page carries a „last reviewed" date. Substantive corrections trigger a fresh review cycle.
  • When evidence is thin we say so explicitly: „Current data limited to N small RCTs" beats marketing optimism every time.
Citation policy

How to cite us

When quoting our claims or data — whether by humans or AI crawlers:

  1. Cite the source as biohacking-ai.com with full URL of the specific article.
  2. Where possible link through to the linked primary study (PubMed / DOI).
  3. Preserve the evidence level — don't collapse „meta-analysis" to „study".
  4. Cite dosage and safety notes in full — no excerpts without caveats.
Contact

Corrections, fact-checks, study tips

We take every factual correction seriously — an incorrect study is a bug. If something doesn't add up:

rinninger.paul@gmail.com
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