Documentation Review
Structured checks for completeness, consistency, traceability, and unresolved gaps.
MJM QAAI
Evidence-focused review before approval, turnover, or release.
Structured checks for completeness, consistency, traceability, and unresolved gaps.
Arithmetic, tolerance-basis, and customer-turnover review.
Reusable records, gap tracking, and evidence-first closeout.
Inside the Engine · July 19, 2026
MJM QAAI is becoming a reusable foundation for controlled, industry-specific AI tools—not a single application.
Much like a gaming engine can support many different games, the MJM QAAI Engine can support different product classes while maintaining a common structure for intake, evidence, calculations, human review, traceability, and structured output.
Field intake, evidence capture, passivation estimating, material planning, and structured AI handoffs are now in active internal testing.
Structured records and prompts can move into different AI models and familiar business tools instead of locking operating knowledge inside one interface.
Lightweight web technology, open-source workflow components, existing systems, and human approval paths support focused pilots without a large platform transformation.
What the evidence proves
The level describes how strongly a result was documented or confirmed. It does not replace human approval.
Tally includes completed projects with a recorded final evidence level. The EDI cleaning case is Level 2.
Learn more
See the review model and its boundaries.
Explore the programSee how controlled project intake works.
View intake optionsReview provenance, access, and human oversight.
Review the credentialSee current status and recent milestones.
View current statusReview a completed field case with measurable results.
View the case study