Graded, never guessed
Three evidence views per compound: community Benefit, linked research context, and the selected observed AE signal where coverage supports it. Cited, or it refuses.
Personal pharmacology lab
Run your stacklike a lab.
Research any supplement, peptide, or longevity compound, inspect community Benefit and observed adverse-event signals where the data supports them, and measure whether it’s actually working for you.
For biohacking, longevity, and serious stacks. Rigor, not hype.
Spin up your labSee it in action
Free to start
Yours, not ours
Encrypted. Member-owned. Export or delete anytime.
Built on real data
Classified user reports, literature, and a knowledge graph.
Platform
One operating system for your whole stack.
From the weekly bench to fully-cited dossiers, every feature turns scattered protocols and bloodwork into grounded, cohort-backed signal.
Decision support, not medical adviceAnimations are simplified; real features are more comprehensive
Why it’s different
A lab that’s truly yours.
The capabilities a serious stack demands, and who actually delivers them.
| Capability | General AI | Supplement DBs | Forums | Your clinician | SelfAssay |
|---|---|---|---|---|---|
| Grades effectiveness and safety, per compound | Partial | Partial | No | No | Yes |
| Real-world outcomes at scale, not just studies | No | No | Partial | Partial | Yes |
| Reasons over your specific stack | Partial | No | No | Partial | Yes |
| Flags interactions across your whole combination | Partial | Partial | No | Partial | Yes |
| Measures whether it's working for you (n-of-1) | No | No | No | Partial | Yes |
| Every claim cited, or it refuses when thin | No | Partial | No | Partial | Yes |
| Calibrated confidence, not false certainty | No | Partial | No | Yes | Yes |
| Private, member-owned data (export & delete) | No | No | No | Partial | Yes |
Each is good at what it’s for. SelfAssay is the only one built to reason over your whole stack with cited evidence, and refuse when it can’t.
Provenance you can see
Truth is in the provenance.
Real-world reports, peer-reviewed literature and a curated knowledge graph, plus clinical trials, pharmacokinetics, adverse-event and FDA-label signals. Every answer is traceable to its source, with its method and sample size shown.
Evidence routed to one answer
Peer-reviewed
114K+
studies
Knowledge graph
186K+
relations
181K+
Classified user reports
114K+
Peer-reviewed studies
186K+
Knowledge-graph relations
How we grade evidence
Rigor you can audit.
Grounding isn’t a tagline; it’s a method. Here’s the standard every answer is held to.
01
Triangulated, not single-source
Every signal is cross-checked across classified real-world cohorts, peer-reviewed literature, and the curated knowledge graph; agreement and conflict are both surfaced.
02
Every claim carries its receipts
Source, method and sample size shown inline. No naked assertions. If it’s stated, you can trace where it came from.
03
Confidence is calibrated
Strength of evidence is graded; weak signals are labelled weak. Precision is never overstated to sound more certain than the data allows.
04
“Not enough data” is a valid answer
When grounding fails, SelfAssay says so plainly, and names what evidence would change the answer. It never fills the gap with a guess.