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MoatDefender

Invented example. Not a company rating.

Example company

An invented team builds agent-guided inspection cells for regulated warehouses. Follow one company from its deck to an investor update.

Follow one invented company through its reading and next actions. This example publishes and registers nothing.

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Drop your deck

PDF up to 5 MB; on Pro and Ultra also PowerPoint (.pptx), Markdown (.md), Excel (.xlsx) or CSV, up to 20 MB. This example starts with the team's inspection-cell deck.

Assess your deck

Read the Moat Index

The number, range and band describe one invented reading. The shape illustrates the advantage’s profile without calculating the index.

Moat deed

58±4

Emerging/Defensible

Illustrative reading. No company has been assessed.

Status
Invented · not issued
Example date
2026-10-16
AI direction
Agentic + physical AI

Example company

Invented Example company Moat Glyph, Moat Index 58 ±4
2D Moat Shape. Radius shows dimension value; outer and inner lines show uncertainty.1234567

Drag or use arrow keys to rotate. Home resets. Rotation pauses on hover or focus. Reduced motion uses a static view. 2D view. Match numbered tips to the values below. Reference line: Moat Index 58. Halo width is ±10 × uncertainty points, clipped to 0–100; it is not a confidence interval.

All supplied dimensions. Values 0–100; uncertainty 0–1.
DimensionGroupValueUncertainty
Brandingpower200.4
Cornered resourcepower550.4
Counter-positioningpower240.4
Network economiespower370.4
Process powerpower310.4
Scale economiespower190.4
Switching costspower650.4

Moat types and AI direction

The team declares three invented capabilities; none establishes verified approval or rights.

Agentic + physical AI

  • Licences & approvals

    Customer qualification and site acceptance take calendar time.

  • Physical & tacit process

    Operators learn how to set up and recover each inspection cell.

  • Rights-cleared data

    The team needs documented rights to retain customer outcome data.

Global MDI context

Compare these types in the published Moat Type Index. Research associations and expected AI durability describe types, without assessing this company or its returns.

Snapshot

Licences & approvals

Evidence
123 associated works507 citing works · 1934–2026
AI durability
holdsPublished expectation
Momentum
+85%2023–2025 / 2018–2020

Agents speed up paperwork, not a regulator's calendar; approvals can still become routine or be revoked.

Physical & tacit process

Evidence
37 associated works701 citing works · 1981–2018
AI durability
dependsPublished expectation
Momentum
Not measuredNo matched research theme

Holds when the know-how lives in physical operations; erodes once it is written down where agents can read it.

Rights-cleared data

Evidence
3 associated works1 citing works · 2004–2016
AI durability
holdsPublished expectation
Momentum
Not measuredNo matched research theme

Exclusive, documented rights do not get easier to copy as agents improve.

Momentum compares average yearly research activity in 2023–2025 with 2018–2020, not market performance. AI durability is an expectation, not a measured outcome. Zero matched works is a coverage gap, not evidence against a moat.

Read 14 types and limits

Build your next move

Try Mark done. The change stays on this page; nothing is saved or published.

1 of 3 example moves done

Example Designer plan

Make the advantage checkable.

Today
58
After new proof
Not projectable

This week: Record the setup sequence and hand it over to a second operator.

  1. 1.Licences & approvals

    Customer qualification and site acceptance take calendar time.

    • Collect the acceptance criteria for one customer inspection site.

      Proof to collect: A customer qualification checklist with a named owner and date.

      This month
      Done 2026-10-16Example customer checklist

  2. 2.Physical & tacit process

    Operators learn how to set up and recover each inspection cell.

    • Record the setup sequence and hand it over to a second operator.

      Proof to collect: A timed handover log, including failures and manual interventions.

      This month

  3. 3.Rights-cleared data

    The team needs documented rights to retain customer outcome data.

    • Document which outcome data the customer allows the team to retain.

      Proof to collect: Customer-approved data rights and retention terms.

      This month
Add the proof in Dropzone

Marking a move done does not change the reading. Add proof and run a new reading.

Find a thesis fit

Compare the declarations with an acquirer’s thesis. Both cards are local examples; neither appears on the public board.

Example company

Emerging

Invented builder · open to partners

Declared capabilities
Licences & approvalsPhysical & tacit processRights-cleared data
AI direction
Agentic + physical AI

An invented acquirer's inspection thesis

Licences & approvals · Physical & tacit process

Agentic + physical AI · Robotics · seed stage · partners or acquisition

Declared criteria align
Capability groups
Aligned
AI direction
Aligned
Open to
Aligned
Band
Aligned
Sector
Aligned
Stage
Aligned

Only declared criteria are compared. Alignment is not an endorsement or a promise of a transaction.

Open Find

Share deliberately

A share card with the same public capability and AI direction. The links share this example and open LinkedIn or X for your review.

Invented share card: licences and approvals, agentic and physical AI. Not a company rating.
LinkedInX
Sample member badge. Invented example; membership not issued and no verification record.

The badge is a sample, not an issued membership or a verification record.

Show what changed

September 2026 → October 2026. Both ARR figures and the comparable readings are invented; the percentage pair is computed from the same example data.

Progress

ARR +10%Moat Index +26.1%
ARR is self-reported. Dash: comparable percentage unavailable or base too low.

The completed move does not cause an automatic increase. A Moat Index change requires new proof and a new reading under the same method.

Create an update