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Enterprise & platforms

Microbiome infrastructure for programmes that need to operate at scale.

For multi-site groups, health platforms and population-scale programmes, the hard problems are consistency, logistics and governance rather than analysis alone. This pathway is about operating a defined proposition reliably across many participants.

Discuss an enterprise programme Explore VAMS ATLAS™ Hospital partnerships

One programme

A single definition, written once

Scope, eligibility, sampling cadence and reporting cycle are set at programme level before any site is onboarded.

Distributed sites and participants

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Sites run independently and at different volumes. What they do not vary is how a sample is taken, routed and analysed.

Coordinated workflow — the narrow point

One protocol
Identical collection instructions and eligibility at every site.
One route
Same kit specification, same transit rules, same laboratory workflow.
One pipeline version
Every sample analysed against the same pinned analysis version.

Programme-level reporting

Comparable across sites because the inputs were

Aggregate, de-identified reporting with site-level breakdowns and participation tracking. Comparability is a property of the shared workflow above it, not of the report itself.

Schematic, not a deployed footprint: site and participant marks are illustrative. Programme reporting is aggregate and de-identified; individual findings stay with the participant and their clinician.

What this pathway is for

If your question is a clinically characterised cohort or a prospective research programme, the hospital pathway fits better. Enterprise is about running something already defined, at scale.

Multi-site healthcare groups

One workflow and one reporting standard across sites that currently do things differently, with results that remain comparable between them.

Health platforms and apps

Microbiome testing and structured reporting behind an existing product, scoped against what integration is genuinely supported.

Employer and member programmes

Population-scale testing where the operational problem is logistics, consent and reporting consistency rather than study design.

Technology partnerships

Data and analytics collaboration where ATLAS is a component of a larger system.

Public and government programmes

Scaled deployments with defined governance, reporting and data-handling requirements.

What actually gets hard at scale

Not the science. These four.

  1. Consistency

    A result produced in one site or cohort has to mean the same thing as one produced elsewhere. Pinned pipeline versions make that checkable rather than assumed.

  2. Logistics

    Kit distribution, collection, chain of custody and sample success rates dominate at scale — they matter more than analytical sophistication.

  3. Governance

    Consent scope, data access tiers, retention and withdrawal handling defined before deployment rather than retrofitted.

  4. Reporting

    What each audience sees — participant, professional, programme owner — and what each is permitted to conclude.

How a programme starts

  1. Scoping conversation What you are deploying
  2. Population and outcome Defined before build
  3. Governance & data handling Consent, access, retention
  4. Integration assessment Against what is supported
  5. Limited deployment One site or cohort first
  6. Review Operational and analytical
  7. Scale decision Continue, adjust or stop
Illustrative programme sequence. Each stage is agreed before the next begins; scale is a decision, not a default.

Scaled deployment describes operational capability, not validated clinical utility. Microbiome outputs remain educational and method-bounded, and do not diagnose, treat, predict or cure.

Discuss an enterprise programme

Tell us about your programme

What you are deploying, roughly how many participants, and where integration matters. Approximate answers are fine.

  1. 1About you
  2. 2Your organisation
  3. 3Programme
  4. 4Context
About you