DATUMKEEP
Four modules · one knowledge engine · AI throughout

The quality intelligence platform for manufacturing.

Investigate failures with AI-guided RCA, monitor your processes with real statistical control, and keep everything your plant learns in one living knowledge base.

LiveRoot Cause Analysis — INC-4821 · seal failureAI DRAFT// sample data
5-Why chain · drafted from evidence4 of 5
1Seal thickness drifted past the upper control limit.SPC · LINE 3 · 08:42 · NELSON 1
2Die-change interval was extended to 12k cycles.MASTER DATA · CONTROL PLAN v4
3The change was never re-validated against capability.PRIOR CASES · KB-1187, KB-0942
4Drafting the next why from lot genealogyREADING · 42 LOTS · 3 DOCUMENTS
Evidence the model read
SPC excursionLine 3 · 08:42
Resolved casesKB-1187 · KB-0942
Control plan v4Die-change interval
Human in the loop
Every why cites the record it came from. Nothing enters the knowledge base until an engineer confirms it.
01 · AI-guided RCA
The modules
What makes them work

Bringing your existing data in? See what imports today →

Not marketing numbers — capabilities shipped in the product today, and verifiable in a live demo.

8/8
Nelson rules evaluated on every control chart
12
statistical tools the AI can run on your data — and none it can fake
5
autonomous detectors, including the one that notices when a sensor goes silent
Day-1 intelligencefrom your embedded knowledgeEffectiveness-scored solutionsrolling out · flag-gatedSPC-grade statistical evidencecontrol charts · capability CIs · Gage R&RMulti-tenant by constructionRow-Level Security
The problem

Extraordinary knowledge generators.
Poor knowledge re-users.

Every shift, your plants produce world-class failure-and-solution knowledge — investigations, corrective actions, hard-won fixes. Then it scatters. Into PDFs, spreadsheets, CMMS tickets, ERP fields, and the memory of an engineer who retires next quarter.

So the same failures get re-investigated from scratch, plant after plant, year after year — as if no one had ever solved them before.

RESOLVED FAILURE · LINE 4 / PRESS #2
Servo overheat → unplanned stop
Root cause found · corrective action verified · 4h 12min downtime recovered
PDF reports
Filed, never searched
Spreadsheets
One per site, no link
CMMS tickets
Closed, then lost
ERP fields
Structured, not legible
Tribal memory
Retires next quarter
From scratch
Investigated again
How it works

Ten scenes. The product, not a pitch.

A walkthrough of the real surfaces — every label, threshold and refusal in it is the shipped product. You click through it at your own pace; nothing plays on its own.

Retrievalone search across three layers, weighted by trust
The enginea capability read the engine refuses to guess at
The refusalseight states where the product declines to answer
About four minutes · no email required
Product tour01 / 10
Why it compounds

The moat isn't a feature. It's the substrate.

A canonical, trusted knowledge core that gets sharper with every analysis.

01

Knowledge that learns, not just stores

A document store gets bigger. DatumKeep is built to get smarter — the effectiveness loop, rolling out today behind a flag, learns from recurrence evidence which solutions actually prevent the next failure.

02

One canonical trusted substrate

Not five disconnected tools. A single de-duplicated Problem → Cause → Solution store every module draws from — RCA, SPC, CAPA and the knowledge base — so trust compounds instead of fragmenting.

03

Built for the floor and the auditor

No-blame by design, fully traceable, export-ready. Engineers trust it because it never points fingers; auditors trust it because every conclusion cites its evidence.

FAQ

Questions, answered.

  • Live: root cause analysis and CAPA, with 5-Why, Ishikawa and 8D supported inside them. Rolling out behind a per-tenant flag: the effectiveness learning loop, and scheduled SPC monitoring. Roadmap, on the same engine: FMEA, reliability and audit workflows. We would rather you knew which is which before the demo than after the contract.

27 questions answered in full — including the ones with an awkward answer. Read the FAQ →

Make the next failure the last one.

Turn the knowledge your organization already generates into a compounding asset — starting with your first analysis.