ZTPL-D Decision Workspace | GSC

Why ZTPL-D Wins

ZTPL-D (Zero Tree Private Label Diaper) is a private-label diaper product designed for regulated retail in 2026.


It delivers Tier-1 SGS results for a tree-free diaper across both open and pant formats, with performance validated at scale. We launched first with ECO-10060, now the global diaper industry standard, openly available and already in use.


This is not positioning. It is execution:


  • Best private-label diaper platform on the market
  • Tier-1 SGS performance results for a zero-tree diaper
  • Validated across open and pant formats
  • First mover and originator of the ECO-10060 global diaper standard


ZTPL-D competes on performance first and wins on system design.

ZTPL-D operates on ECOs (Electronic Compliance Objects) and is deployed across three global hyperscalers to meet enterprise-scale retail, audit, and ESG requirements:


  • AWS (Frankfurt & London) for production scale and continuity
  • Microsoft Azure (Paris) as the ESG authority and sovereign anchor
  • Google Enterprise Cloud (Madrid) for high-throughput distribution supporting EU and LatAm retail flows


This architecture supports large-volume data continuity, real-time verification, and global rollout without friction.


BUILT FOR TODAY — AND THE NEXT 15 YEARS


ZTPL-D is hyperscaler-native by design.
Logs align. Proof resolves cleanly. No firewalls. No SaaS overlays. No vendor lock-in.


The platform integrates directly into existing private-label SKUs, planograms, and retail workflows. It meets today’s ESG and procurement requirements and is already aligned with what enterprise stacks will demand over the next decade.

Zero trees. Zero SaaS. Zero friction.  That is why ZTPL-D scales — and why buyers don’t have to explain it internally.

Procurement Review Questions:


  1. Can this run at 200–500 containers, continuously, without escalation?
  2. Can this be defended under audit, legal, and board review?”
  3. Does approving this private-label system  introduce new IT risk, or reduce it?
  4. If deployed across additional banners or regions, does ZTPL-D support on-demand manufacturing and diaper conversion capacity (OEM-C) — without requiring re-approval or re-tooling?
  5. Does this decision resolver (ECO-10060) integrate cleanly with SAP, Oracle, and other ERP-native procurement workflows — without custom code, plugins, or ongoing maintenance?
  6. If approved in one market, does this decision resolver (ECO-10060) support deployment across additional markets (EU, LATAM, USA, Canada) under a single governed decision state — without altering commercial, pricing, or sales processes?
  7. If ZTPL-D is a private-label diaper — and not an ESG platform that replaces legal or IT systems — does it prevent ESG escalation by resolving the orderability decision (ECO-10060) for a private-label diaper SKU under current regulatory conditions, before Green Claims, CSRD, EUDR, or UK RTS issues reach audit, legal, or board review?

ECO-10060 Hyperscaler Stack — Built for Enterprise Trust

ZTPL-D does not rely on a single cloud or a single narrative. It runs on a multi-cloud, single-truth architecture designed to mirror procurement reality.


Primary Sovereign Anchor — Microsoft Azure (EU / FR)

Role: Jurisdictional root for ECO-10060, including FR-ECO-10060.


Why it matters to buyers and execs:
→ Enterprise-grade identity and policy control
→ Audit-grade, append-only posture
→ EU sovereignty alignment (region + compliance expectations)
→ Native adjacency to SAP procurement and governance patterns


Azure is the boardroom-safe anchor where “Can this be defended?” questions end.

Secondary Compute & Distribution — Google Cloud (Madrid, ES)

Role: EU expansion rail for speed and resilience.


What it does:


→ Distributes machine-readable proof objects (JSON / JSON-LD)
→ Handles high-volume resolution lookups
→ Provides redundancy without altering canonical truth


Why Madrid:
EU-wide reach, low latency, and regional resilience — without changing what is true, only how fast it is accessed. Supports EU and LATAM retail access patterns by increasing speed and resilience, without acting as a jurisdictional authority or source of truth.

Model Distribution Surface — Multi-Cloud LLM Availability

Role: Compute, never authority.

Models run wherever enterprise teams expect them to:


→ Azure AI Studio
→ Google Cloud Model Garden
→ Other enterprise LLM endpoints as required


Hard rule:


Models do not author truth.


They only compute, format, or resolve against deterministic ECO-10060 objects.


This prevents “AI said so” risk.

How Decisions Actually Resolve (Human + Machine)

Machine-Facing Resolution

→ ERP or AI procurement agent ingests SKU / GTIN
→ Pings owned shorthand surface (e.g.,  eu-eco.org/... )
→ ECO-10060 returns a deterministic state:


 ORDERABLE / RESOLVED / RESTRICTED

→ Proof anchors returned inline
→ Decision resolves without escalation

Human-Facing Review (Only If Needed)

→ Humans access jurisdiction-explicit surfaces
(e.g.,    eu-eco-10060.org   ,   fr-eco-10060.org   )


→ Used for:

  • legal text
  • audit context
  • anything near the SAP “BUY” button


Machines decide. Humans audit. No one debates PDFs.

Sovereignty + Enterprise Trust

The Azure sovereign anchor aligns with how boards, legal teams, and IT departments evaluate risk in FR/EU environments.


Jurisdiction, identity, and audit posture are explicit, defensible, and familiar to enterprise procurement and governance teams. This removes internal hesitation before it starts.

Redundancy Without Truth Drift

Google Cloud (Madrid) provides scale, speed, and regional resilience without introducing a second source of truth.


Canonical objects remain append-only and versioned, while distribution expands independently. Availability increases without compromising control.

ERP Adjacency

The architecture mirrors how procurement actually operates inside SAP-native environments. Systems ingest deterministic states first; humans step in only when audit or legal review is required. This eliminates debate loops and internal rework.

Summary: Proof Separated from Narrative

Proof lives on governed, machine-resolvable surfaces independent of messaging or presentation. As branding, markets, or positioning evolve, evidence remains stable and accessible. This protects buyers from narrative drift and escalation risk.



Result: ZTPL-D advances through procurement quietly and predictably — and buyers stay out of escalation.