Augury Logo


Stability Above All
United States
< $10m
11 - 50
Open website

Alluvium puts Machine Learning to work to help industrial customers achieve operational stability and perfect their production. We have developed a computing platform that is designed to turn massive streams of complex machine and operator data into simple, real-time insights. At the core of our platform is our proprietary Stability Score™, which combines state-of-the-art, real-time Artificial Intelligence with expert human interpretation. Our products support both front-line industrial operators and back-office data analysts who need to understand the stability of their operations at all times because stability means safe, efficient, and optimal production. Alluvium’s flagship product is called Primer, which leverages the power of our real-time Machine Learning platform for AI-assisted forensic analysis:

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Augury is a provider of Industrial IoT analytics and modeling, and functional applications technologies.
Analytics & Modeling
Machine Learning
Real Time Analytics
Functional Applications
Enterprise Asset Management Systems (EAM)
Use Cases
Asset Health Management (AHM)
Machine Condition Monitoring
Predictive Maintenance
Augury’s Technology Stack maps Augury’s participation in the analytics and modeling, and functional applications IoT technology stack.
  • Application Layer
  • Functional Applications
  • Cloud Layer
  • Platform as a Service
    Infrastructure as a Service
  • Edge Layer
  • Automation & Control
    Processors & Edge Intelligence
  • Devices Layer
  • Robots
  • Supporting
  • Analytics & Modeling
    Application Infrastructure & Middleware
    Cybersecurity & Privacy
    Networks & Connectivity
Technological Capability
Number of Podcasts3
EP33a: Stability of an oil refinery = S&P 500 index — An Interview with Drew Conway of Alluvium
Wednesday, May 23, 2018

What is the similarity between stability and the S&P 500 index? How can we use data to identify fire risks and where to best open a coffee shop in New York City? 

From using regression to identify fire risks in New York City to managing complex process control, it all comes down to getting the right information to the right person at the right time to make a decision. Drew explains what stability means, and the tension between  machines and people as it pertains to data. 

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EP33b: Machine learning is not a magic box that takes data and gives magic findings — An Interview with Drew Conway of Alluvium
Thursday, May 24, 2018

Where within the chain of operation in an industrial company is the best place to insert a piece of software? Is a bus system just a bunch of big computers moving around on wheels? Does machine learning hold the answer to maximising the value of each interaction between humans and software? Are we all data engineers regardless of what our name card states?

Drew explains how to take heterogenous data streams and distill it into a stability score that is an index of operations and produce high value alerts. We also explore human machine interaction to build a model more effectively than a fully unsupervised method.


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EP33c: How to engage customers and prove your value? — An Interview with Drew Conway of Alluvium
Sunday, May 27, 2018

How to engage customers and speed up the sales process? How to get a sale out of a production plant fire? How should you price SaaS so that it encourages engagement and referrals? How to identify who isn’t pulling their weight on a power grid system?

Drew explains his sales philosophy and lessons learnt. We also explore a few case studies that makes use of Alluvium Primer to increase data processing and decision making speed from months to minutes.


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