Monthly Archives

April 2017

Falkonry Webinar on Control Global

By | IT/OT Management

Webinar: Using Patterns in Real-Time Data for Operational Excellence

Hosted by Control Global, Presented by Falkonry

May 17, 2017 at 2pm ET

Register Now
Manufacturing and utilities companies are challenged with increasing the performance of their assets amid an aging infrastructure, retiring workforce, and rapidly changing technology.  Falkonry has uncovered a new way of working with existing automation and control architectures to provide predictive insights using time-based pattern recognition, fed from real-time data.

Falkonry works with your staff, leveraging their resident knowledge, to provide context and meaning to the patterns. It ‘institutionalizes’ learning, using both artificial intelligence and machine learning, enabling continuous improvement for operations. This webinar will discuss how users are better able to predict downtime, maximize uptime, yield and quality using pattern recognition technology.

After viewing this webinar, visitors will take away:

  • What is pattern recognition?
  • How can pattern recognition help me in my every day operations?
  • How long will it take to see benefits?
  • How easy is it to start?
  • How have others used pattern recognition in their operations?

Meet our Speaker:

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Nikunj Mehta
CEO & Founder
Falkonry

Nikunj Mehta
started Falkonry in 2012 under the belief that operational excellence comes from thorough and up-to-the-minute understanding of system conditions. Nikunj gained experience with operations and analytics challenges at the world’s largest and most sophisticated industrial organizations at C3 Energy as its Architect and VP of Customer Success.

Nikunj has a Ph.D. and M.S. in Computer Science from USC, and a B.E. in Computer Engineering from University of Mumbai. He has contributed to standards at both W3C and IETF.

Sponsored by:
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Register Now!

Solution fit and flexibility: why Falkonry product teams invest time in redesigning their UI

By | IT/OT Management

Solution fit and flexibility: why Falkonry product teams invest time in redesigning their UI

A series on product improvements at Falkonry – Part 1

By Jeegar Shah – Sr. Director Products,  Falkonry

 

When designing a complex product that has all the bells and whistles under the hood, it is imperative that the user experience be all the more simplistic, streamlined and intuitive.

As any product evolves to encompass new ideas and optimizations, there is a tendency to display the prowess of your algorithmic horsepower to your users by giving them YAF (Yet Another Feature). This is all dandy for developers that have an exploding cache of Github repos and code checkins as they try their one upmanship on their colleagues with cumulative pull requests. But this is often a nightmare for customers who are asymptotically approaching their steady state of product usage and now have to deal with YAF – when they never really asked for one.

At Falkonry, our overarching objective is solution fit and flexibility. We believe that the promise of bringing OT (Operations Technology) efficiency lies in the ability to empower subject matter experts (SMEs) with the tools to make timely and effective decisions. A YAF may exactly help you achieve the opposite. Falkonry is committed to making AI-based pattern recognition an easy-to-incorporate component of any operations-oriented solution. With the addition of every algorithmic richness and IP, we enforce a mindset of looking back at our footsteps to remind us of the silhouette of an army of SME’s that will be following the same steps and pausing every so often to ask each other the question “Did we just throw a YAF?”

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Now published on CIO Online: Enterprise IoT: Top-down > Bottom-up

By | IT/OT Management

An article by Falkonry’s Sr VP of Products, Greg Olsen, was recently published in CIO Online. The topic? Whether to start an #IoT (Internet of Things) project from the bottom-up, or the top-down.

Greg’s premise is that most companies start from the bottom-up: beginning with the sensors/hardware, building the infrastructure and integration, and then eventually bringing that data and information into the enterprise-level systems. He feels that this approach, although widely used, may not always be the right approach.  IoT is a rapidly changing technology, and for most companies, a project-based (‘top down’) approach might better meet the companies’ goals.

Per Greg: “Your primary challenge today and then, is that the IoT solution ecosystem is still very immature. There is a vast set of rapidly evolving technology building blocks that need to be understood and correctly assembled. There are far too few solution architects and designers who know how to build solutions. Not only do we need more providers due to growing demand, but because of the inherent diversity in IoT solutions, we will require greater specialization among system integrators, VARs, and other solution providers.”

For the entire story, click here.

Repost: How Infrastructure as a Service (IaaS) Can Help You in Your ‘Shark Tank’ Moment

By | Uncategorized

This blog post, written by Oracle’s Thomas Bressie, Vice President, Oracle Cloud, discusses the dilemma many small to medium sized businesses face when trying to scale their business from an IT perspective.  Bressie refers to it as the “Shark Tank” moment, when a major event (IPO, publicity, etc.) drives workload demand ‘through the roof.’

An Infrastructure as a Service (IaaS) cloud platform might be the best option for these businesses.  The scalability, elasticity and response to demand spikes offer a cost-effective way for computing.  @Falkonry is called out as a provider of #AI solutions using a hybrid cloud IaaS.

To read the blog post in its entirety, please go here.

Visual Goodies in Falkonry’s Learning

By | IT/OT Management

The learning capabilities of Falkonry can be pretty addictive because they are so visually gratifying. Now to round out that Learning & Monitor interface, we added a few nifty features.

Improved Condition Summary

Increased visual capabilities

 

You can now quickly find out which elements are in a given condition(s) in a given period of time, so that you can navigate directly to those events. A dog-eared pull-out is available on all summary blocks so that you can see which conditions occur in that block of time and which events are in that condition, and for how much of the time. You can select the events you want to investigate further so that you can quickly assess the findings of a condition in a period of time.

This new feature will enable you to evaluate how conditions arise across your data set and what patterns are discovered by Falkonry in that data. When dealing with large numbers of things this feature will improve your ability to inspect Falkonry’s findings without losing context of the overall problem.

Improved Condition Buttons

This works in combination with the condition selections, which we have further simplified by reducing all unlabeled conditions to a circular buttons and user-named conditions to rounded corner rectangular buttons. Additionally, you only see buttons for conditions you are currently looking at. You can always bring in additional condition timelines from the selection panel by choosing old classifications or new verification, etc.

There are other usability improvements that provide you the information you are looking for, removing delays such as:

  • Increased the amount of vertical screen space available for viewing by removing the fixed navigation bar
  • Reduced the lag between creating a pipeline and being able to access the pipeline for learning
  • Added the ability to inspect your data just before starting the learning process
  • Auto-updating of the histories of flow segments and learning in the Configuration view

Analytics Performance Improvement

On top of all these visual improvements, the speed of the analytics was improved so that your model revisions complete faster and with fewer and more understandable errors.

These improvements are iterative steps we’ve taken to increase performance and interoperability. We’ll continue to work on increasing connections to a variety of data sources, providing greater manageability of pipelines, as well as improving the learning and monitoring interfaces. All of this is to improve reliability, performance and intelligence.

This post was originally written March 6, 2016