Create Time,
Not Waste

In today's fast-paced world, supply chain complexity exceeds human capacity. Each decision has uncertain outcomes with economic and environmental consequences.

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Our Purpose

Helping People Make Better Use of Their Time and Resources

Time is life's most valuable asset, which is why we aim to help people save time through easier, faster, high-quality decision-making that improves utilization of supply chain resources.

OUR PRODUCT

AI-First Supply Chain Planning

We are redefining supply chain analytics, decision-making, and human-machine interactions.

#1

AI Prediction Platform

for Prediction Accuracy

A data centric, domain specific, model agnostic platform built specifically for supply chain practitioners to generate accurate predictions without needing to consult data scientists or develop coding skills.

AI Enabled Decision System

#2

A decision system purpose-built to combine the computational power of AI predictions with human judgment for enabling enterprise adoption and continuous improvement of decision quality, speed, and confidence.

for Decision Quality

AI Agency & Human Control

#3

A framework of AI agents with specialized tools, knowledge bases, and problem-solving architectures that automates routine tasks while allowing humans to maintain control over supply chain planning processes.

for Efficiency and Automation

Our deep knowledge in supply chain and practical experience with AI projects creates the perfect foundation to tackle today's problems.

1. AI Projects Don't Deliver Promised Value

Despite $26B in planned investments by 2025, only 13% of AI projects reach production. Today, AI investments are utilizing domain-agnostic technology that relies heavily on data scientists who are manually coding and conducting experiments.

83% of executives are dissatisfied with supply chain technology investments.

WHY YOU NEED NOODLE

2. Supply Chain Planning Isn't Working Efficiently

Advanced Planning System (APS) software employs outdated algorithms that ignore real-world uncertainties, favoring single values over probability distributions. This oversimplification results in unrealistic plans and operational chaos. Even after significant ERP and APS investments, organizations often return to Excel for planning, struggling against departmental silos and sluggish decision processes.