Continuous Genomic Intelligence
Rewise Health is the precision-health intelligence platform for companies. We read genomes, blood, wearables and lifestyle together — continuously — and ship the results as APIs, white-label reports and turnkey programs your members experience under your brand. Calibrated for Indian biology.
01 — The problem
Each stream is collected in isolation, read in isolation, and acted on in isolation. The signal that matters lives in the intersection — and no one is reading it.
02 — The platform
The genome is the constant; everything else is the stream. Rewise ingests both, harmonises them, and runs them through population-calibrated models that surface what is relevant — per person, per use case, continuously.
Data-agnostic by design. Any accredited lab, any wearable, any record system. Structured, harmonised and de-identified on ingestion.
Millions of datapoints in; ranked, explainable signals out. Every signal traces to a named pathway — mTOR, SIRT1, NF-κB, PER2 — never a black box. Models normalised on 3.5 billion+ annotated, longitudinal datapoints from a proprietary Indian cohort.
You ship the experience your members already trust — now powered by genomic intelligence. No genomics team, no model risk, no cohort problem.
03 — The software
Excerpts from live One.Age report and dashboard surfaces. Partners see the full platform on a demo — this is the shape of what your members receive.
Trajectory · 4.7 years
Teal: biological · dashed: chronological — the gap is the product.
Panel verdict
105 of 115 optimal · 10 flagged · 5 improving since last draw. Each marker cross-read against genotype before a protocol is issued.
Ranked priorities
Every system age links to its drivers, its pathway, and this quarter's protocol — inside your app or ours.
// POST /v1/signals { "member": "mb_4xk…", "inputs": ["genome", "panel_115", "wearable"] } // 200 — ranked, explainable { "signals": [ { "id": "methylation.folate", "rank": 1, "evidence": ["MTHFR C677T het", "folate 0.82"], "protocol": "methylfolate 800–1000 µg/d", "retest_days": 90 }, …
04 — The reasoning
Biological age headlines one report; recovery capacity another; a hormonal transition a third; a disease that hasn't happened yet, the fourth. Rewise doesn't hand back a generic report — it ranks what matters for this individual and traces every conclusion from genome to intervention to a measurable outcome.
For him, the ranked signal is methylation: MTHFR C677T plus folate at 0.82 ng/mL. Protocol issued — methylfolate 800–1,000 µg daily — retest in 90 days. Biological age is the scoreboard, not the story.
Same engine, entirely different signal set. For her, biological age is irrelevant — recovery and the iron gate are the levers. The genome says 2:38–2:42 marathon; the bloodwork says close the iron gate first.
Single hormone tests look “normal” — the signal is variability over time crossed with a slow-COMT estrogen-metabolism genotype and rising bone-turnover risk. Protocol: strength training 3×/wk, vitamin D repletion, quarterly hormone cadence, clinician consult — years before standard care reacts.
For him the signal is the slope, not the level — Indian biology runs a decade ahead of the reference ranges. Protocol: resistance training, fibre-first meal sequencing, 120-day retest. Standard care intervenes at 6.5%; the genome said start at 31.
05 — Intelligence domains
Partners license the domains their members need. Each runs on the same reasoning layer — genome, blood and lifestyle read together, traced to mechanism.
Women's health is decided by hormones read against genetics and time — and it is the most underserved intelligence problem in health today. Reference ranges built on male cohorts miss it; Rewise reads it natively, across every life stage.
For women's-health platforms ready to own the category.
Insulin sensitivity, weight response, diabetes risk — a decade earlier in Indians, read a decade earlier here.
Lipids, inflammation and pressure traced to genotype — ApoB and Lp(a) behaviour the panels alone can't explain.
Trainability ceilings, recovery capacity, injury susceptibility — the athlete chain above, productised.
Micronutrient status, food response and supplement protocols grounded in nutrigenomics, not quizzes.
Microbiome composition read against diet, genotype and inflammation — the gut as a driver, not a buzzword.
Biological age, system ages and ageing-pathway signals — the scoreboard for everything above.
04 — Why population matters
Most genomic models are trained on European-ancestry cohorts and quietly lose accuracy on Indian genomes. Reference ranges, risk thresholds, ageing clocks — all drawn from someone else's biology. Rewise was built the other way around: population-specific first, data-agnostic and globally scalable second.
The Rewise answer
Every ageing clock and polygenic risk score is normalised against 3.5 billion+ annotated, longitudinal datapoints from a proprietary Indian cohort — restoring the sensitivity and specificity that imported models lose. Genomic analysis finally reading the right population.
Cohort composition and scale are disclosed under NDA. The architecture stays data-agnostic — the same calibration discipline extends to any population as partner data grows.
07 — Outcomes
Not technology — results. Each partner type integrates Rewise for one commercial reason. Here it is, plainly.
New high-margin SKUs from samples you already run — no wet-lab build, no bioinformatics hires, no model risk.
Buys → new revenue per existing sample · One.Age product line · clinician-ready reports
Life-stage programmes — PCOS, perimenopause, menopause — built on hormonal intelligence none of your competitors can replicate from quizzes.
Buys → category leadership · defensible personalisation · premium-tier pricing
Quiz-based plans churn. Plans grounded in a member's genome and bloodwork — with a retest loop — keep them subscribed.
Buys → lower churn · higher LTV · a reason to retest every quarter
Readiness, recovery and trainability signals turn coaching from opinion into evidence — and into a premium product tier.
Buys → premium tiers · athlete outcomes · coach credibility
Continuous signal-tracking between visits — ranked priorities and explainable mechanisms clinicians can act on and defend.
Buys → pre-symptomatic detection · preventive revenue line · member loyalty
Dynamic cohort stratification and outcome-driven One.Age+ programmes — engagement that shows up in claims and absenteeism.
Buys → claims-relevant stratification · measurable programme outcomes
09 — The One.Age line
A product ladder built on the same intelligence layer. Partners start where their data starts, and climb as depth pays for itself.
Everything above is available as an API and as white-label report infrastructure — POST /v1/signals in, ranked explainable intelligence out. Annual One.Age+ programmes for corporates and insurers run on the same rails.
10 — Scientific foundation
Every signal is mechanism-first: correlated to the hallmarks of ageing and traced to named molecular pathways, so a clinician — or a regulator — can follow the reasoning end to end.
08 — Defensibility
Every partner adds multimodal, longitudinal, population-specific data. Every datapoint sharpens the clocks. Sharper clocks produce better outcomes; better outcomes bring more partners. The moat is not the model — it is the compounding cohort no one else is building.
11 — Common questions
Partner with Rewise
Tell us what you're building. We'll show you the platform live — your use case, real signals, and the fastest route from your data to your first intelligence-powered release.