AI Workflows Built to Measure
Most companies adopt AI without knowing if it's working. I design and implement human-in-the-loop AI workflows with built-in measurement, aligned to frameworks like NIST AI RMF and ISO 42001 — so you can prove ROI, reduce risk, and scale what works.
Bringing 15 years of data-driven marketing, behavioral science, and statistical testing methodology to how businesses implement AI.
Book a Free AssessmentLatest Articles
All articles →- Decision Intelligence: What Marketing Teams Actually Mean When They Say 'Data-Driven' Most 'data-driven' decisions aren't. Here's the framework for building systems that actually improve decisions over time.
- Why Most A/B Tests Fail Before They Start The statistical and process errors that invalidate most experiments before a single visitor lands — and what to do instead.
Free Tools
All tools →- A/B Test Statistical Significance Calculator Calculate whether your A/B test results are statistically significant using a chi-square test. Supports one-tailed and two-tailed testing with up to 3 variants.
- Chi-Square Test Calculator for CRO Test whether conversion rates differ significantly across multiple groups — traffic sources, page variants, segments, and more. Fixed at 95% confidence.
- Minimum Detectable Effect (MDE) Calculator Find the smallest effect size your A/B test can reliably detect given your sample size, baseline rate, and desired statistical power.
- Sample Size Calculator for A/B Testing Calculate the minimum sample size needed per variation before launching your A/B test, based on your baseline conversion rate and MDE.
- Welch's T-Test Calculator Compare the means of two independent groups with unequal variances. Ideal for revenue-per-visitor, average order value, and other continuous metrics.