ZeroMan.ai
Volume 01 · The Coordination Problem
ZeroMan.ai · Governed decision layer for Consumer Goods supply chains

Turn supply-chain signals into governed action.

ZeroMan.ai coordinates exceptions, constraints, scenarios, approval rules, and prepared actions into one traceable operating loop — across the systems and teams your supply chain already depends on.

An AI-driven, agentic autonomous supply-chain system — built to sense disruptions, reason through trade-offs, and prepare execution across your existing enterprise stack under explicit decision rights and governance.

Map a decision loop See the platform logic

Conceptual preview showing incoming supply-chain signals moving into ZeroMan's governed decision layer and leaving as policy-aware prepared actions.

Signal-to-action flow
Incoming signal nodes
demand spike
supplier delay
service-risk alert
ZeroMan
Governed decision layer
decision stateException triage
scenario engine3 policy-safe paths
governance gateApproval rules active
approval thresholdHuman sign-off required
Prepared actions
approval packet
supplier expedite request
production resequence note
Sense
Decide
Optimize
Govern
Execute
Learn
Conceptual flow · not live production telemetry
Current stage
Stage
Design-partner phase
Platform
In design and build
Default autonomy
prepare and recommend; named humans approve

Best first loops

  • supplier delay response
  • replenishment exceptions
  • MRP exception resolution
  • expedite approvals

Public assets

Platform BriefGovernance ModelReference Models

Not claimed

  • customer deployments
  • certifications
  • measured production outcomes
Decision gap

The missing layer is not data. It is governed decision coordination.

Enterprise systems record what happened. Planning tools show what could happen. Teams still coordinate what should happen next across meetings, spreadsheets, approvals, and disconnected workflows. ZeroMan turns that coordination into a governed decision loop.

Systems of record

what happened

ERP, WMS, TMS, MES, and finance systems preserve operational history and accountability.

Planning tools

what could happen

APS, MRP, and planning models expose possible outcomes, constraints, and trade-offs.

ZeroMan.ai

what should happen next under governance

A governed decision layer prepares the next operating move while keeping decision rights visible.

ZeroMan is designed to sit across and above ERP, APS, WMS, TMS, MES, and finance systems. It does not replace them, and it is not another dashboard; it coordinates the decision work between them.

Coordinates

  • exceptions
  • constraints
  • scenarios
  • decision rights
  • prepared actions
  • learning traces
Decision run theater

Watch a disruption become a governed recommendation.

A packaging supplier delay enters as a signal. ZeroMan frames constraints, compares scenarios, checks approval rules, and prepares the action packet for named human review.

Illustrative decision run — not a customer deployment or measured-result claim.

Packaging supplier delay threatens priority SKU availability in the next production window. Expedite above threshold requires director approval. Prepare an expedite request for the delayed packaging lane, resequence the affected production slot, and route director approval before action.

01 · Signal

Disruption detected

Supplier-delay signal is tied to the priority SKU, timing window, and availability risk.

02 · State

Decision state assembled

Service target, inventory coverage, production slot, logistics cost, and threshold policy are bound to one run.

03 · Scenarios

Trade-offs compared

Protect service, minimize cost, and balanced recommendation are evaluated side by side.

04 · Gate

Governance checked

The expedite threshold triggers director approval before any execution path is advanced.

05 · Recommend

Recommendation prepared

The balanced option becomes the governed recommendation with approval context attached.

06 · Prepare

Action packet assembled

Supplier, planner, production, finance, and leadership artifacts are prepared as one packet.

07 · Learn

Trace captured

Service impact, cost variance, recovery path, and approval latency remain attached for future runs.

Recommendation

Balanced recommendation

Prepare an expedite request for the delayed packaging lane, resequence the affected production slot, and route director approval before action.

Prepared actions
  • supplier expedite request
  • planner action packet
  • production resequence note
  • finance impact memo
  • leadership approval summary
Learning trace
  • service impact
  • cost variance
  • inventory recovery
  • approval latency
Coordination graph

The coordination graph behind every supply-chain decision

One exception rarely belongs to one function. It moves across demand, supply, manufacturing, logistics, finance, commercial teams, leadership, and enterprise systems. ZeroMan turns scattered handoffs into one traceable decision state.

Before

  • fragmented handoffs
  • disconnected approvals
  • spreadsheet/email/manual escalation

ZeroMan state

  • one decision state
  • policy-aware recommendation
  • prepared actions
  • named approval owner
  • traceable outcome

Demand, supply, procurement, manufacturing, logistics, finance, commercial, leadership, and enterprise systems converge into one governed decision loop before prepared actions are released.

Governed decision loop
Governance layer → Prepared actions
Teams
  • Demand Planning
  • Supply Planning
  • Procurement
  • Manufacturing
  • Logistics
  • Finance
  • Commercial
  • Leadership
Systems
  • ERP
  • APS
  • WMS/TMS
  • Supplier Portal

Governed decision loop

Demand, supply, procurement, manufacturing, logistics, finance, commercial, leadership, and enterprise systems converge into one governed decision loop before prepared actions are released.

  1. Governed decision loop
  2. Governance layer
  3. Prepared actions
  1. one decision state
  2. policy-aware recommendation
  3. prepared actions
  4. named approval owner

Conceptual operating-layer view. Nodes show where coordination occurs; they do not claim live integrations or production deployments.

Governed autonomy

Autonomy with decision rights built in

ZeroMan does not skip governance to move faster. It uses governance to make faster decisions safe: every recommendation carries context, thresholds, approval paths, and a trace.

Signal + context → Threshold check → Named approval → Prepared action → Trace preserved.

Governance gate

Named approval

Signal + context
System does
Threshold checkGovernance requirement
Prepared action
Prepare and recommend with human approval
Named approval
Trace preserved

Policy examples

  • Expedite cost above threshold → director approval
  • Service-risk exception above threshold → leadership visibility
  • Inventory write-off → finance approval
Current/default posture
L2/L3

Prepare and recommend with human approval

L2

Prepare

L2/L3
System does

Assemble options, trade-offs, and action packets.

Governance requirement

Policy, risk, cost, service, and timing constraints are attached before anything moves.

Human decision right

Humans choose whether the prepared packet is valid and ready for recommendation.

Technology logic

A decision layer, not another screen

ZeroMan is designed as an operating architecture for decision loops: signals become structured decision state, feasible scenarios, policy checks, prepared action packets, and learning traces across the systems teams already use.

Explore product architecture

Signal plane → Decision state → Scenario engine → Governance policy → Action preparation → Learning trace. Selected primitive: Signal plane.

Decision object pipeline

Conceptual architecture view. The homepage model describes operating primitives, not a claim of completed enterprise integrations.

  1. input01

    Signal plane

  2. object02

    Decision state

  3. compare + policy03

    Scenario engine / Governance policy

  4. packet + trace04

    Action preparation / Learning trace

Structured decision object
signal

signal = capture(exceptions, constraints, risk)

state = structure(context, owner, thresholds)

scenario = compare(service, cost, time, inventory, risk)

policy = apply(thresholds, approvals, escalation)

packet = prepare(action, owner, evidence)

trace = record(decision, outcome, learning)

Selected primitive

Signal plane

P01 · input
Role in the decision object
Separates decision-relevant signals from background operational noise before a loop starts.
Input
Exceptions, constraints, risk signals, demand changes, and supply changes.
Output
Normalized signal set with source, time, owner, and affected decision loop.
Governance relevance
Keeps provenance visible so later recommendations can be traced to specific inputs.
First decision loops

Start with one decision loop

ZeroMan starts where coordination work is already expensive: recurring exceptions, trade-offs, approvals, and prepared actions that cross functions.

Loop 01

Supplier delay response

Trigger
Critical component delay threatens priority SKU availability.
Functions
sourcingplanningmanufacturinglogisticsfinance
Governance
When does expedite cost require director approval?
Prepared actions
  • supplier escalation
  • resequence proposal
  • cost memo
  • approval packet
Map this loop
Loop 02

Replenishment exception

Trigger
Store or DC coverage falls below target while demand remains active.
Functions
replenishmentdemand planningsupply planninglogisticscommercial
Governance
Who approves a service-protecting move that raises transport cost?
Prepared actions
  • transfer recommendation
  • order adjustment
  • coverage note
  • planner packet
Map this loop
Loop 03

MRP exception resolution

Trigger
MRP creates expedite, reschedule, or shortage messages that need business context.
Functions
materials planningprocurementproduction planningfinancequality
Governance
Which exception can be auto-prepared, and which needs planner or manager review?
Prepared actions
  • exception bundle
  • supplier note
  • schedule change request
  • risk summary
Map this loop
Loop 04

Expedite approval

Trigger
A late order, component, or finished good can recover service only through premium action.
Functions
planningprocurementlogisticsfinanceleadership
Governance
What cost, margin, or service threshold requires named approval?
Prepared actions
  • expedite request
  • cost comparison
  • service impact note
  • approval summary
Map this loop
Loop 05

Inventory service-risk trade-off

Trigger
Inventory is available, but serving one commitment creates risk for another channel or region.
Functions
supply planningcommercialfinancecustomer serviceleadership
Governance
Who can approve service protection when it increases inventory or margin risk?
Prepared actions
  • trade-off brief
  • allocation option
  • finance impact memo
  • leadership summary
Map this loop
Loop 06

Production resequencing

Trigger
A constraint or urgent demand shift requires changing the production sequence.
Functions
manufacturingplanningprocurementqualitylogistics
Governance
When does a schedule change need plant, planning, or commercial approval?
Prepared actions
  • resequence note
  • capacity impact
  • material readiness check
  • stakeholder packet
Map this loop
Loop 07

Logistics cost/service trade-off

Trigger
A shipment can hit service with higher cost, or protect cost with service risk.
Functions
logisticsplanningcustomer servicefinancecommercial
Governance
What service-risk level justifies premium freight or lane change approval?
Prepared actions
  • routing option
  • premium freight memo
  • customer promise update
  • approval packet
Map this loop
Loop 08

Allocation under shortage

Trigger
Constrained supply cannot satisfy every customer, channel, or market commitment.
Functions
demand planningsupply planningcommercialfinanceleadership
Governance
Which policy decides allocation when service, margin, and strategic accounts conflict?
Prepared actions
  • allocation recommendation
  • customer impact summary
  • exception rationale
  • leadership approval brief
Map this loop
Founder / operator credibility

Built from the coordination reality ZeroMan is meant to govern.

ZeroMan starts from how supply-chain decisions actually move: across teams, constraints, escalation paths, and prepared actions. Founder Kaan Porsuk brings senior supply-chain operating experience, marketplace and direct-fulfillment exposure, and doctoral research on managerial delegation to AI.

  • Senior supply-chain operating background
  • Marketplace and direct-fulfillment exposure
  • Doctoral research on managerial delegation to AI
  • Coordination reality before generic AI demos
Read founder story
Choose your path

Choose the path that matches your intent.

Different visitors need different next steps. Each route preserves source context so operators, evaluators, reviewers, investors, press, and talent land in the right flow.

Path 01

Design partner

Bring one recurring coordination problem and map a governed decision loop.

Start design-partner track
Path 02

Technical evaluator

Review how signals, scenarios, governance, and prepared actions fit together.

View platform logic
Path 03

Governance reviewer

Understand decision rights, approval thresholds, and responsible autonomy.

Review governance model
Path 04

Investor

Request access to the investor data room.

Request access
Path 05

Press or analyst

Access company background, approved boilerplate, and media resources.

Visit press room
Path 06

Talent

Help build the governed decision layer for supply chains.

View careers
Governed autonomy starts with one loop

Bring one decision loop.

Start with a recurring exception, approval path, or cross-functional trade-off. ZeroMan maps the signals, constraints, scenarios, governance rules, and prepared actions around it.

Default posture: prepare and recommend; named humans approve.

Map a decision loop Read the platform brief