Introducing Phizzle’s
EDGMaker Software Stack
The first enterprise-class software stack designed specifically for edge computing
Making it Possible to Automate & Rely on IoT Devices in Mission-Critical Environments

What is the EDGMaker Stack?
The EDGMaker Software Stack technology relies on innovations in Regenerative Engineering to solve the dual challenges of edge ecosystems—low powered devices and high volume data surges. EDGMaker’s 5x improvement in computing power is critical to helping engineers and first responders save lives, save money, and save the environment through its patented and proprietary software solutions.
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The EDGMaker Software Stack
The EDGMaker Connector System
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Bring all your IoT data online
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Onboard new machines in 10 days
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Create more robust and accurate datasets

The EDGMaker Data Management Platform
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Seamless integration with native platforms including
AWS, Microsoft Azure, and MySQL -
Gain visibility into entire ecosystem of edge machines
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Visually monitor outcomes for faster learning

The EDGMaker Decision Engine
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Efficiently process edge data at industrial scale
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React to data surges in near-real time
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Reduce the likelihood for human error w/ automation
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Achieve annual OpEx savings in reduction of human labor, maintenance, safety, and compliance

TECHNICAL BENEFITS
EDGMaker’s Regenerative Engineering Solution
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Rely on IoT Devices to Operate with Server-Grade Performance
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Efficiently process edge data at industrial scale
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Enable 200W server-grade performance on 40W edge devices
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Solve for low-power devices and constraints; achieve 80% IoT workload reductions
Loop Closure on Full IoT Systems for Decision-Makers
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Gain visibility into entire ecosystem of edge machines
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Monitor live environments and enact responses in near-real time
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Improve system speed and policy through machine learning
Device Agnostic Installation
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Easily integrate with AWS, Microsoft Azure, MySQL, and other native systems
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Asset-data model enables device onboarding in less than 24 hours
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Partner access to Phizzle’s proprietary data management platform (DMP)
Never-Off in Mission-Critical Environments
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Live system updating through MQTT
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Guarantee 24/7 connectivity
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No downtime during surges
BUSINESS BENEFITS
EDGMaker’s Competitive Advantage




What is Regenerative Engineering?
Regenerative Engineering is a technical breakthrough in network infrastructure - the first resilient and self-optimizing IoT software designed to tackle the dual challenges of edge computing: low-power devices and high volume data surges.
TENET #1
Principle of Exclusion
IoT evaluation workload is done through effective edge filtering. Apply the PRINCIPLE OF EXCLUSION to edge computing devices in order to:
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Filter incoming edge data
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Efficiently compute small-records
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Reduce logic to what’s most important to the outcome
TENET #2
Closing the Loop
Bring VISIBILITY to data surges because, counter-intuitively, regenerative algorithms perform more optimally with more data:
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Optimize edge feedback
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Capture more & new data
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Visually monitor outcomes for faster learning
TENET #3
Anti-Parsing
Software logic/architecture isn’t PARSED in a traditional, serialized way, enabling:
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On-the-fly maintenance & updates
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Maximized efficiency of local resources
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Never Off 24/7 Connectivity
To request a copy of Phizzle’s 2020 Edge Computing White Paper, please provide your verified email address below. If you’d like more information or to schedule a consultation with Phizzle, we are happy to discuss IoT software solutions—reach out to our team at sales@phizzle.com

Phizzle CTO Ryan Brady performs a technical whiteboard session on Regenerative Engineering—the software innovation transforming pharmaceutical manufacturing by removing manual processes to automate and digitize edge devices for true IoT connectivity.
Key topics include: edge computing, regenerative engineering, automation, artificial intelligence, flexible data formatting.
Ryan Brady, Phizzle CTO: Regenerative IoT Systems for Pharmaceutical Manufacturing
Watch How Phizzle’s IoT Edge Decision Engine Changes the Landscape for Real-time Anomaly Detection with Transportation and Connected Vehicles
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Processing is 100% dictated by configuration that describes the environment
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Automates trigger detection and handling to determine reaction to data-driven circumstances
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Our algorithm provides speed and scale—this demo shows 390 microseconds to process a single vehicle report in a resource constrained environment
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Our IoT Edge Decision Engine detects any hazard or future hazard and alerts the driver in sub millisecond timing