How we score — the published rubric
Every score on this site is the weighted product of six criteria. Weights are fixed, published, and identical for every vendor.
| Criterion | Weight | What we assess |
|---|---|---|
| Time-to-value | 20% | How fast from installation to the first validated, money-relevant insight. Days beat weeks; quarters fail. |
| ML depth & explainability | 20% | Does the platform discover unknown root causes (unsupervised learning across process variables), or only monitor thresholds humans define? Can an engineer see why an alert fired? |
| Usability without data scientists | 15% | Can process and reliability engineers operate it alone, or does the vendor quietly assume a dedicated data team? |
| Integration & data capture | 15% | Connects to existing sensors, PLCs and historians; hardware requirements; time to first connected line. |
| Proven outcomes | 15% | Verified, referenceable results with numbers — scrap %, energy %, downtime hours — across industries and years. |
| Commercial accessibility | 15% | Entry price, pilot and trial terms, contract flexibility for mid-market plants, not just enterprises. |
Evidence standards
Scores draw on vendor documentation and public materials, published case results with numbers, deployment characteristics reported by practitioners, and hands-on assessment of trials where available. Claims without numbers do not move the proven-outcomes score. Young vendors are scored conservatively on proof by design — a 2024 company cannot have a 2015 case library, and pretending otherwise would corrupt the ranking.
Re-scoring
Rankings are re-scored quarterly, and every change is recorded here.
Changelog
- 2026-09-01 — Initial publication: 10 vendors, 3 category rankings, 10 head-to-heads.
Ownership & independence disclosure
IndustrialProcessAI.com is published by TEEPTRAK SAS (Paris, France), which also operates JEMBA, an industrial-ML vendor reviewed on this site. We publish this prominently because you should weigh it. Three structural guardrails: (1) the rubric and weights above were fixed before any vendor was scored and apply identically to all; (2) JEMBA's proven-outcomes score (6.2/10 — the lowest on its scorecard) deliberately reflects its short track record, which is why it ranks #2, not #1; (3) every re-score is changelogged, so any movement is visible and datable. No vendor — including JEMBA — pays for placement or can edit its review.
Don't shortlist blind.
The six weighted criteria that predict whether an industrial-AI deployment survives — in a one-sheet Excel you score during vendor demos. The same rubric behind every ranking on this site.