01 / 04
Read.
Literature, preprints, trials and public omics, unified into a living knowledge graph of aging biology.
An AI scientist that works on aging, around the clock.
wit.bio reads the literature, connects multi-omics data to the hallmarks of aging, proposes testable hypotheses and designs the experiments to validate them — so your team spends its time at the bench, not in the backlog.
ASK IT ABOUT
senolytics
partial reprogramming
NAD+ metabolism
rapalogs & mTOR
REASONING ACROSS ALL 12 HALLMARKS OF AGING
12
hallmarks of aging
24/7
research, around the clock
Genomic instability
Telomere attrition
Epigenetic alterations
Loss of proteostasis
Disabled macroautophagy
Deregulated nutrient sensing
Mitochondrial dysfunction
Cellular senescence
Stem cell exhaustion
Altered intercellular communication
Chronic inflammation
Dysbiosis
Interventions
SenolyticsPartial reprogrammingRapalogsNAD+ precursorsAutophagy inducersMitochondrial therapeuticsGene therapyAnti-inflammatories
THE PROBLEM
Aging is the most complex system in biology — twelve interlocking hallmarks, thousands of new papers every month, data scattered across species and tissues.
Discovery still moves at human speed.
No single team can hold it all in their head. Promising targets get missed, and good hypotheses wait months for a test.
wit.bio is a tireless research partner that does the reading, the connecting and the planning — with a full evidence trail your scientists can audit.
HOW IT WORKS
A closed scientific loop — always running, always auditable.
02 / 04
Hypothesize.
Ranked, mechanistic hypotheses, each linked to the evidence for — and against — it.
03 / 04
Design.
Protocols with model systems, controls and aging readouts, ready for your lab or a CRO.
04 / 04
Learn.
Results flow back in, beliefs update, and the next round of experiments gets sharper.
FIG.1 — HALLMARK × INTERVENTION MATRIX
Reasoning across all 12 hallmarks of aging
Illustrative evidence density · hover a cell to trace hallmark × intervention.
LIVE RESEARCH RUN
Watch it think.
From a one-line objective to a protocol your team can run — every step visible, every claim sourced.
Illustrative example run.
Restore autophagy in aged hepatocytes
Synthesizing literature & public omics
Mapped to disabled macroautophagy · nutrient sensing · mitochondrial dysfunction
H1 · mTORC1 ↓ → TFEB nuclear translocation
H2 · Spermidine → EP300 inhibition
H3 · Urolithin A → mitophagy
Model — primary hepatocytes, young vs aged mice
Readouts — LC3-II flux (± bafilomycin A1), p62, TFEB localization
Controls — vehicle, rapamycin positive control
Protocol ready for review
Open protocol →
CAPABILITIES
Built for the specific questions of longevity science.
01 — FIG.2 AGING CLOCK
Aging clocks & biomarkers
control
intervention arm
biological = chronological
Illustrative data.
02 — KNOWLEDGE GRAPH
Target discovery across the hallmarks
NAD+AMPKmTOR
NF-κBSIRT1FOXO3
PGC-1αp16TFEB ★
03 — RANKED HITS
Compound & repurposing search
rapamycin
spermidine
urolithin A
04 — ORTHOLOG MAP
Cross-species translation
Worm
Fly
Mouse
Human
05 — ISOLATED
Your data stays yours
Private datasets remain in your workspace — never used to train shared models.
06 — PROVENANCE
Every claim, traceable
TFEB activation rescues autophagic flux in aged liver[1][2], consistent with mTORC1 inhibition data[3].
WHO IT'S FOR
For teams that want more shots on goal against aging.
A
Longevity biotechs
Expand your pipeline and de-risk programs before committing capital to the lab.
B
Academic aging labs
Turn a small team into a much larger one: faster reviews, sharper grants, better-designed studies.
C
Investors & foundations
Diligence the science behind longevity programs with an evidence-backed second opinion.
EARLY ACCESS
Give your lab a scientist that never sleeps.
We're onboarding a small group of longevity teams as design partners. Tell us what you're working on.
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No spam. Just a conversation about your research.