Azirella
Decision Intelligence Platform for Supply Chain

AI agents that make decisions, not just recommendations

Autonomy is the first purpose-built Decision Intelligence Platform for supply chain — modeling, orchestrating, monitoring, and governing every planning decision with autonomous AI agents. 20-35% cost reduction with full explainability and human override.

Strategic · Weekly
S&OP
Policy parameters θ · Cross-functional alignment · Risk scoring · Demand-supply balancing
Tactical · Network · Daily
Demand Planning
Forecasting · Sensing
Tactical · Network · Daily
Supply Planning
MPS · MRP · Sourcing
Tactical · Network · Daily
Inventory Optimization
Buffers · Rebalancing
Operational · Shift
Plant A
Cross-function trade-offs
Operational · Shift
DC West
Urgency modulation
Operational · Shift
DC East
Causal coordination
Operational · Shift
Plant B
Bottleneck detection
Operational · Shift
DC Central
Synergy signals
Execution · <10ms
ATP
Execution · <10ms
PO
Execution · <10ms
MO
Execution · <10ms
TO
Execution · <10ms
Quality
Execution · <10ms
Maint.
Execution · <10ms
+5 more
Context & guardrails down Feedback & outcomes up 4 layers · 11 agents · 20-35% cost reduction

Five Layers of Decision Coordination

Information flows down as policy and directives, back up as signals and outcomes. Each layer operates at its natural time horizon.

Strategic Consensus

Layer 4 · Weekly

Analyzes supply chain topology — bottlenecks, concentration risk, fragility — and computes policy parameters that shape all downstream behavior.

4

Network Coordination + Cross-Authority

Layers 2-3 · Daily + Ad Hoc

Generates daily site directives — demand forecasts, exception probabilities, priority allocations. Cross-functional trade-offs resolve at machine speed via the authorization protocol.

2-3

Site Cross-Agent Coordination

Layer 1.5 · Hourly

Learns causal relationships between 11 agents at each site. Predicts cascade effects — a production spike will create quality load hours later — and pre-adjusts urgency before the cascade unfolds.

1.5

11 Execution Agents

Layer 1 · <10ms per decision

Specialized agents execute narrow decisions at machine speed: ATP, purchase orders, rebalancing, manufacturing, quality, maintenance, and more. Coordinated via biologically-inspired signal propagation.

1

From 847 Exceptions to 14

What happens when an enterprise planner arrives Monday morning.

A planner arrives to 847 exceptions across the network. Autonomy's agents have already evaluated every one. By the time she opens her dashboard:

780

Auto-Resolved

Within guardrails, no human needed

53

Informational

Handled, flagged for awareness

14

Need Judgment

Ranked with trade-off analysis

0

Missed

Every exception evaluated

She spends her morning on the 14 decisions that actually need human expertise — cross-functional trade-offs, novel supplier situations, strategic pivots. Each one arrives pre-analyzed with ranked options and full balanced scorecard impact. Every override she makes teaches the system for next time.

Adoption Builds Trust Through Measurement

Week 1

~45%

Auto-executed decisions

Week 12

~72%

Auto-executed decisions

Steady State

~85%

Auto-executed, <10% overridden

A Decision Intelligence Platform, Not a Planning Tool

Autonomy implements Gartner's full DI lifecycle — model, orchestrate, monitor, govern — natively for supply chain.

🎯

Decisions as First-Class Assets

Every recurring decision — stocking, ordering, allocating — is a trackable digital asset with defined inputs, logic, ownership, and measured outcomes. Not an implicit output of a planning run.

🔄

Full Decision Lifecycle

Model, orchestrate, monitor, and govern decisions end-to-end. From decision modeling through agent execution to outcome tracking and continuous learning.

📈

Measured Maturity Progression

Progress from Support to Augmentation to Automation — governed by measured decision quality, not arbitrary trust thresholds. Override effectiveness is measured and tracked statistically.

🔍

Full Explainability

Every AI decision comes with reasoning grounded in specific data: this order, this inventory level, this lead time. Ask Why at any point in the decision chain.

🛡️

Guardrail Governance

Set business rules — max order value, min service level, cost ceiling. Agents act within bounds automatically and escalate what exceeds them. Every override teaches the system.

🔗

Domain-Native Intelligence

Purpose-built for supply chain with 35 AWS SC entities, 11 specialized agents, and 21 distribution types. Not a generic DI platform that requires customization.

Built for Enterprise Scale

11
Autonomous Agents
20+
Distribution Types
<10ms
Decision Latency
35
AWS SC Entities

Grounded in Research & Industry Frameworks

Autonomy's architecture draws from Gartner's Decision Intelligence framework, peer-reviewed research, and proven decision science.

Gartner Decision Intelligence

DIP Framework (2026)

Autonomy implements Gartner's full DI lifecycle: decision modeling, orchestration, monitoring, and governance. 50% of SCM solutions will use intelligent agents by 2030.

Sequential Decision Framework

Decisions Under Uncertainty

A unified framework for decision-making under uncertainty. Four policy approaches — rules, optimization, learning, and simulation — structure our five-layer agent hierarchy.

Decision Science

From Information to Action

Decision Intelligence as the discipline of turning information into better actions. Analytics, statistics, and ML unified through decision quality, not just prediction accuracy.

Compact Neural Architecture

Purpose-Built Execution Agents

Small, focused models that outperform general-purpose AI on structured supply chain reasoning. Purpose-built for speed and reliability at the execution layer.

Confidence Guarantees

Distribution-Free Bounds

Every agent decision carries a calibrated confidence interval. When confidence is low, decisions route to higher-tier reasoning automatically.

Causal Decision Modeling

Levers → Intermediaries → Outcomes

Decisions as digital assets with explicit causal chains from levers through intermediaries to outcomes. Every execution agent maps to a formal causal decision model.

Ready to see Autonomy in action?

See how autonomous AI agents transform supply chain planning from reactive firefighting to proactive governance.