FlowOps’ Problem Solved Utilizing Explainable AI

James Dargan

Alleviating Headaches

One can never refute — especially for those professionals working in the logistics industry — how maintaining reliable delivery schedules is vital to the world of time-sensitive supply chain management.

In the era of globalization, this is more important than ever before. Advances in deep technology, especially in artificial intelligence (AI) and machine learning (ML), are alleviating some of the headaches with innovations like AI software for manufacturers called Flow Operations, FlowOps for short.

And it just so happens that one startup, Noodle.ai, is the world leader in this technology, designing AI-enabled applications for enterprise and industry.

FlowOps, a category of AI software that aims to eliminate operations entropy across an entire supply chain, from raw materials to shelf.

 — Noodle.ai

The San Francisco-based company was founded in 2016 by Martha McGaw, Matt Denesuk, Raj Joshi, Stephen Pratt, and Ted Gaubert, and in the five years has raised a total of $72 million in funding, with financial backing coming from the likes of Dell Technologies Capital and TPG Growth.

These venture capital firms see Noodle.ai’s IP as obviously addressing sensitive pain points in supply chains and distribution systems, and believe — somewhere down the line — their initial investment will pay off big time.

The company can also boast of winning awards such as Top 10 companies to work for (LinkedIn), Forbes Top 50 “Most promising AI Companies”, and Gartner Cool Vendor, adding more prestige to it.

Noodle.ai

According to data on the startup’s website, distribution problems amount to some $446 billion being stranded in supply chains (Hackett Group 2019 Capital Survey), with the average stockout rate in fast-moving consumer product companies at 10% with 75% of stock-outs due to systemic errors (Thomas Gruen & Daniel Corsten) with downtime amounting to an incredible $689 billion disappearing when the lines went down (International Society of Automation, 2018)

To be even more pessimistic, the real cost in manufacturing of poor quality products is a massive $861 billion (ASQ, 2018), not helped by, as Noodle.ai puts it,

“traditional software being [a] jumbled alert storm.”

And that’s where FlowOps can help, assisting manufacturing and supply chain in a number of ways:

  • Manufacturing

Eradicate quality defects and specification variability. Banish unplanned downtime. FlowOps in manufacturing keeps the most critical assets humming and enables your team with a new generation tools for improving quality and yield.

  • Supply Chain

Defeating operations entropy in the supply chain starts with a top-notch demand signal, but doesn’t end there. Better predictive visibility into supply imbalances and deploying just the right amount of goods into the network minimizes waste and keeps balance sheets lean.

Noodle.ai does this by using state-of-the-art data science powered by Explainable AI (XAI) to process large amounts of data, identify patterns, forecast results that can ultimately improve business performance through its five products of Asset Flow, Quality Flow, Demand Flow, Inventory Flow, and Production Flow.

The founding and executive team are made up of individuals from top firms in data science, enterprise software, consumer goods, manufacturing, and AI.

Stephen Pratt is the CEO and Co-Founder of Noodle.ai. With a passion for building great teams to apply maths and science to create great products at the intersection of ML, AI, and advanced analytics, he started off as a consultant in the 1980s and has an MS in Satellite Communications from George Washington University.

President, COO and Co-Founder is Raj Joshi. Like Pratt, Joshi is a seasoned consultant, having worked for the likes of Deloitte and Infosys during his more than a thirty-year career. He has an MS in Chemical Engineering from the University of Akron and an MBA from the University of Texas at Arlington.

Martha McGaw is Chief Talent Officer, as well as Co-Founder, and was educated at the University of California, Davis. Starting off her career as an HR manager and consultant at Deloitte, prior to co-founding Noodle.ai McGaw was a Global Human Resource Leader at Infosys.

With a Ph.D. from the University of Arizona in Materials Science and Engineering, Matt Denesuk is another Co-Founder of the startup but left in 2019 for the Royal Caribbean Group, his current company. Having built two other data, analytics and AI organizations from scratch, he worked for IBM for fifteen years.

Ted Gaubert is a Co-Founder and former CTO of the startup. A globally recognized technology thought leader, innovator, and disruptor, he is now serving as CTO of Global Product Engineering at Dun & Bradstreet, a leading provider of data, analytics, SaaS, and API products. Gaubert is credited with coining and trademarking Enterprise AI™ as well as defining Enterprise AI™ as a market category. Gaubert obtained a Ph.D. in Engineering from the University of Texas at Austin.

With its Explainable AI improving supply chain and manufacturing performance by syncing and exploring massive time-series data, both structured and unstructured, internal and external while reducing waste at the same time, Noodle.ai is set to grow its already large customer base and prove deep tech solutions like AI is the only way to go.

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