Funded-event GTM trigger · Real NIH RePORTER data

A newly-funded NIH grant is a lab
about to spend.

Every week, thousands of US labs win new NIH awards. Each one triggers a wave of equipment, reagent, software, and CRO purchasing over the next one to two quarters. LabLeads turns that public, dated, funded event into a clean sales trigger: the institution, the grant size, the likely purchasing category, and the spend window — delivered the week the money lands.

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The reframe

Research databases tell you who published. We tell you who just got paid.

Dimensions and GrantForward are built for researchers chasing the next grant. Nobody packages the award onset as a buying signal for the vendors who profit when that lab spends. That's the gap. A $2.1M R01 in genomics means a lab is about to evaluate sequencers, library-prep kits, and bioinformatics. We surface that the moment the notice posts.

Institution + grant

Org name, city/state, award amount band, notice date, funding institute, activity code. Real RePORTER records.

Likely category

Title/abstract/terms classified into the equipment & reagent categories that grant is about to buy in.

Spend window

The 0–6 month purchasing window after the award, with the ~Q1 peak — so reps reach out before the budget is committed.

Privacy by design. We sell the signal — institution, grant, category, window — and, where public, the PI's name and title. We never sell or scrape personal contact data (no emails, phones, or home addresses). Your team sources outreach the way it always has. GDPR/CCPA-safe by construction.

Honest demand read

What this is — and isn't.

This is a B2B lead-trigger feed for lab-equipment, reagent, scientific-software, and CRO sales teams. The economics are clean: one converted equipment sale dwarfs the subscription. The honest caveats: it's a cold-B2B lead feed (adoption is a sales motion, not viral), and the value is in the onset event, not deep historical analytics — though a real funded-onset archive accrues here daily. The data underneath is 100% real NIH RePORTER; nothing is mocked.