Canvas Category Software : Information Technology : Asset Performance Management

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Primary Location Cupertino, California, United States

Financial Status VC-A; Presidio Ventures, Basis Set Ventures, Polaris Partners, Start Smart Labs, Zetta Venture Partners

Falkonry was founded with the mission to enable step improvement in operational excellence through data and computation. Today, Falkonry’s predictive operations solutions are used by companies, both large multinationals & regional manufacturers, to power their digital transformation & achieve significant improvements in production uptime, quality, yield and safety. Just like an expert eye, Falkonry can discover insights hidden in your operational data and deliver timely, actionable intelligence. We empower our users — plant personnel, process or maintenance engineers, line operators, analysts — to make better operational decisions with evidence-based approaches.

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IFS to acquire Falkonry AI

📅 Date:

🔖 Topics: Acquisition

🏢 Organizations: IFS, Falkonry

IFS, the global cloud enterprise software company, today announced it has signed a definitive agreement to acquire Falkonry, Inc. a California-based Industrial AI software company that provides automated, high-speed data analysis to the manufacturing and defense industries. The AI-based, self-learning solution continuously monitors large volumes of data for assets, machines, systems, and industrial processes to discover and analyze unusual behavior and causes of failures.

Headquartered in California, USA, and regional presence in Mumbai, India, Falkonry was founded in 2012 by CEO Nikunj Mehta. The company has customers across North America, South America, and Europe, including the US Navy and Air Force, Ternium, North American Stainless, Harbour Energy, and SSAB, demonstrating its focus on industries in industrial manufacturing and Defense agencies.

Read more at PR Newswire

U.S. Navy Takes Falkonry AI to the High Seas for Increased Equipment Reliability and Performance

📅 Date:

🔖 Topics: Anomaly Detection

🏭 Vertical: Defense

🏢 Organizations: Falkonry, US Navy, Oracle, NVIDIA

Falkonry today announced a big leap for Falkonry AI with the Office of Naval Research deploying its AI applications to advance equipment reliability on the high seas. This AI deployment is carried out with a Falkonry-designed reference architecture using NVIDIA accelerated computing and Oracle Cloud Infrastructure’s (OCI’s) distributed cloud. It enables better performance and reliability awareness using electrical and mechanical time series data from thousands of sensors at ultra-high speed.

Falkonry has designed its automated anomaly detection application, Falkonry Insight, to take advantage of Edge computing capabilities that are now available for high security and edge-to-cloud connectivity. Falkonry Insight includes a patent-pending, high-throughput time series AI engine that inspects every sensor data point to identify reliability and performance anomalies along with their contributing factors. Falkonry Insight organizes the information needed by operations teams to determine root causes and automatically informs operations teams to take rapid action. By inserting an edge device into the US Navy’s operational environment that can process data continuously, increasingly sophisticated naval platforms can maintain high reliability and performance out at sea.

Read more at Falkonry Newsroom

Where is 'The Edge' and why does it matter?

📅 Date:

✍️ Author: Nikunj Mehta

🔖 Topics: Edge Computing

🏢 Organizations: Falkonry

The Edge is not a place – It is an optimization problem. Edge computing is about doing the right things in the right places. As with all optimization problems, getting to the “right” answer requires considering a number of tradeoffs that are specific to your situation and then applying the right technology to maximize the benefits for the cost you are willing to pay.

Part of what makes Edge confusing is that definitions of “The Edge” tend to focus on technologies rather than on use cases. Since use cases span a very wide range of requirements and the boundaries between those use cases don’t map directly to technologies, definitions in terms of technology can be difficult to use.

Read more at Falkonry Blog

AI-based operational excellence in steel manufacturing

📅 Date:

✍️ Author: Shreebhooshan B

🏭 Vertical: Primary Metal

🏢 Organizations: Falkonry

Modern steelmaking is heavily instrumented with several process parameters being monitored, yet there are limited operational insights available in real-time. Take, for instance, the continuous casting process − a facility producing 150 tonnes per hour can generate over US$5 million per day in production revenue, assuming current steel prices. Conversely, a single day of lost production is equivalent to US$5 million worth of losses. Therefore, a manufacturer can unlock tremendous value by eliminating these unscheduled production downtimes.

Casting molten steel, unsurprisingly, is hard on heavy equipment. Components wear under harsh conditions leading to failures or adverse product quality. Early detection of such conditions could warn the maintenance and production managers to schedule repairs before failures occur. Applying advanced analytics to machine and process data can help in predicting such unwanted events. Data-science projects are often designed for specific use cases thereby limiting the scope and interoperability of the model. The approach faces challenges in terms of model sustenance in production and scalability across use-cases or plants.

Read more at Falkonry Blog

Assisting Continued Process Verification with AI

📅 Date:

✍️ Author: Chris Lee

🔖 Topics: continued process verification

🏭 Vertical: Pharmaceutical

🏢 Organizations: Falkonry

Patterns of behavior reflected in the data from equipment sensors can give insight into these performance affecting factors. In many cases, these patterns develop before product quality is significantly affected. Putting in place analytics that can detect these patterns gives the plant operations team actionable warning before CPV limits indicate a problem. This warning can be used to limit costly production impacts. Importantly, because the CPV process itself is untouched, these kinds of pattern detection analytics can be implemented without additional filings or regulatory delay. Assisting CPV does not mean replacing or even changing CPV.

Read more at Falkonry Blog

Integrating Falkonry with Azure IoT

📅 Date:

✍️ Author: Phagun Baya

🔖 Topics: MQTT, IIoT

🏢 Organizations: Falkonry, Microsoft

Falkonry Clue applies advanced analytics to multivariate time-series data to discover meaningful patterns. This valuable operational data is supplied to Clue’s powerful AI engine by leveraging Microsoft Azure’s IoT infrastructure. Clue is designed to fit seamlessly into Azure’s reference architecture thereby easing the integration process.

Connecting the plant to the cloud, the Azure IoT Hub acts as a bi-directional communications brain for all connected IoT devices – managing data transfers, updates, setting up credentials for every device, and defining access control policies. These connected devices include OPC UA enabled sources such as most SCADA systems that support the MQTT protocol for data transfer.

Read more at Falkonry Blog

AI Solution for Operational Excellence

📅 Date:

🔖 Topics: Manufacturing Analytics, Cloud Computing

🏢 Organizations: Falkonry, AWS

Falkonry Clue is a plug-and-play solution for predictive production operations that identifies and addresses operational inefficiencies from operational data. It is designed to be used directly by operational practitioners, such as production engineers, equipment engineers or manufacturing engineers, without requiring the assistance of data scientists or software engineers.

Read more at AWS Marketplace

Falkonry Secures Series A Funding to Optimize Industrial Throughput, Quality and Yield With Operational Machine Learning

📅 Date:

🔖 Topics: funding event

🏢 Organizations: Falkonry

Falkonry, Inc. the leading provider of operational machine learning for Global 2000 industrial companies, today announced that it has raised $4.6 million in a Series A funding round. This round brings the total funding raised by Falkonry to $10.9 million. The Series A round is led by Presidio Ventures, the early stage venture capital arm of Sumitomo Corporation. Fortive Corporation, a diversified industrial growth company, has also joined the round as a strategic investor. The early seed stage investors will enhance their existing investment positions in Falkonry, and include Basis Set Ventures, Polaris Partners, Start Smart Labs and Zetta Venture Partners.

Read more at BusinessWire