Know your IR before you field.

Structured intake. Real sources. Deterministic math. Your incidence estimate, delivered to your inbox in minutes — without asking an LLM to guess a number.

Research my Incidence
Method
How it Works
Primary action
Research my Incidence
Output
View Sample Report
200Targetable criteria in DB
Tier 1Federal probability surveys
~2 minEstimate delivered by email
0LLM-generated numbers
FreeFirst 5 estimates

How it works.

AI interprets your text. Deterministic math and real databases calculate the number.

01

Describe the study

Enter the work email, select the audience type, then define core qualifiers and any layered screening criteria.

02

AI parses the text

A language model interprets the audience definition into structured criteria. It does not generate the estimate number.

03

Databases do the math

Structured criteria are looked up against federal probability surveys and provider-approved datasets with deterministic logic.

04

Sourced report by email

A concise report with IR range, feasibility, confidence, and source-level breakdown is delivered to your inbox in minutes.

What the report looks like.

Numbers you can defend, sources you can cite, and a feasibility read you can send to your sample team.

Estimate · v1

Among U.S. adults 30+ with Type 2 Diabetes, nationwide.

Feasible
Incidence rate
Low9.2%
Mid11.4%
High13.1%
Confidence HIGH
Age 30+Census ACS
Type 2 DiabetesNHANES · BRFSS
Nationwide, U.S.Census ACS
Recommendation: Feasibility is strong for standard Rx-adjacent screens. If you need diagnosed and on prescription treatment, expect IR to drop 2–4 points.

Built on sources you would defend to a client.

Three tiers of evidence. Deterministic logic. No LLM-generated numbers.

Tier 1

Federal probability surveys

  • Census · ACS
  • NHANES
  • BRFSS
  • NHIS
Tier 2

Syndicated & provider-grade

  • MRI-Simmons
  • Major panel targeting databases
  • CDC WONDER · registry data
Tier 3

Peer-reviewed supplements

  • Peer-reviewed journal prevalence figures
  • Publicly available registry snapshots
  • Triangulation when Tier 1 / 2 coverage is thin
Deterministic boundary: An LLM parses your text into structured criteria. The numbers themselves come from lookup, math, and documented logic — not generation.