Products DMAIC Intelligence Copilot
Lean Six Sigma statistics, explainedTell the copilot what you want to know: do two lines differ, is the process capable, did the change actually work. It checks normality, picks the right statistical test, runs it, and explains the decision in plain English. The step every belt second-guesses in Minitab, done in under a minute. Then take the whole DMAIC project from charter to control in the same workspace.
Belts spend weeks on slideware while the method quietly breaks down where it matters most.
So projects drag on — and the savings never show up in the P&L.
A guided DMAIC project workspace that keeps the method honest: structured phases, exit-gate criteria, a real statistics engine, and an AI Master Black Belt that separates facts from assumptions and refuses to over-claim.
Start with the statistics: paste your data, ask a plain question, and the copilot picks the right test, runs it, and explains the decision. Every step is auditable and nothing is computed by an AI guess. Then run the whole DMAIC project in the same workspace.
Capture the project on one workspace, run the numbers without leaving it, and get an evidence-based review at every gate — while a qualified human stays the decision-maker.
Say what you want to know and paste your data. The copilot checks normality, picks the right test (t-test or Mann-Whitney, ANOVA or Kruskal-Wallis, paired t or Wilcoxon), runs it, charts it, and shows its reasoning step by step. Under a minute, and every choice is auditable.
Readiness, Data Quality, Root-Cause Confidence, and Control Sustainability scores — with “Do Not Proceed Until” blockers that stop the project skipping ahead.
Descriptive stats, Anderson-Darling normality, Pareto, Cp/Cpk & sigma/DPMO, I-MR / X-bar & R / p / np / c / u control charts, run charts, 1-sample, 2-sample and paired t-tests with confidence intervals and effect sizes, Mann-Whitney, Kruskal-Wallis, Wilcoxon, ANOVA, chi-square, 2-proportion and regression. Every result carries a plain-English read-out: what it says, what it does not prove, and the next decision.
Define → Measure → Analyze → Improve → Control, with field-level prompts that build the charter, problem and goal statements, plans, and control plan as you go.
SIPOC, a DMAIC roadmap, a root-cause evidence map, and an FMEA — built on a drag-and-drop canvas and exported with the project.
Flags weak thinking, correlation-as-causation, and missing measurement-system analysis — and recommends DMAIC, A3, Kaizen, or just-do-it when that fits better.
Bring a charter or deck in from Word, Excel, PowerPoint, PDF, or screenshots — with AI extraction, a confidence score, and a human review step before anything loads.
A branded project deck and report — charts, scorecards, canvases and statistics included — ready for the tollgate read-out and the project file.
Most tools store the project.
DMAIC Intelligence improves the thinking.
It is not a forms package. Every statistic is computed deterministically in code, never guessed by an AI. The copilot checks normality before choosing a test, blocks an analysis when the data does not fit, separates facts from assumptions, and never claims significance or savings without the evidence, keeping a qualified Belt in control.
Shaped by 16 years leading Lean Six Sigma, Operational Excellence, and continuous improvement programs across pharma, biotech and electronics manufacturing — with statistical rigor, risk, and sustainment built in.
Start with the stats copilot for $19/mo, cancel anytime. Then take the whole project from charter to control in the same workspace.