blueproof.ai turns connected-fixture activity, a documented without-project baseline, and a versioned calculation into one source-linked record. The evidence travels with the result so an owner, reporting team, or independent reviewer can see how it was produced.
The first call should be about the site: which fixtures are connected, what data is available, what baseline evidence exists, and what a verifier would need to check the work.
Connected-fixture activity, reported use, identity, and product context anchor the project side.
The source evidence stays separate from the modeled baseline, while the method, assumptions, exceptions, and calculation remain attached.
The output gives a reporting team or reviewer a path from the result back to the project evidence.
For diligence, we can walk through a sample receipt, data-flow diagram, VWBA 2.0 mapping, and claims-language guardrails.
Water reporting frameworks distinguish direct measurement from calculations, estimates, and models. They also ask for the methods and assumptions needed to understand the figure. A gallon total without that context is incomplete.
Sustainability information is increasingly prepared for internal controls and independent assurance. The reviewer needs to follow the result through its boundary, source evidence, baseline, method, assumptions, and exceptions.
Specifications show what was planned. Invoices show what was installed. Utility data shows the whole building. Fixture platforms show how connected products operate. A reported project outcome still needs those records organized around one defined project and period.
The record preserves where measurement ends and modeling begins, then carries the method and calculation forward. Recomputability is useful because a reviewer can test the claim without reconstructing the project from memory.
Connected-fixture activity and reported project use describe what happened after installation. The without-project baseline remains a model supported by separate evidence.
blueproof.ai does not collapse those into one “measured savings” number. It shows the basis of each input, preserves the method and assumptions, and makes the resulting avoided-withdrawal estimate rerunnable.
That discipline turns recomputability into something practical: a reporting team can support the result, and an independent reviewer can challenge it.
A water-demand-reduction method mapped to WRI's voluntary VWBA 2.0 guidance, with explicit project boundary, baseline, assumptions, and claim limits.
An authenticated integration tested against Sloan's SC Argus Pro sandbox for locations, devices, fixture activity, reported water use, and product context.
A running platform that binds source-reading hashes, baseline basis, method version, assumptions, data-availability decisions, and calculation into a signed project record.