SUPPLIER MANAGED

Seebo

Industry 4.0 SaaS Platform
Israel
2012
Private
< $10m
51 - 200
Open website

Seebo is an Industry 4.0 SaaS platform with laser-focused business solutions that ‘move the needle’ for manufacturers in 3-months or less.

Founded in 2012, the company has raised over $22M from Viola Ventures, TPY Capital, Pritzker Group, and other investors. Seebo was named a Gartner Cool Vendor in the Internet of Things for 2017.

You can learn more by visiting our website: seebo.com or introduce Seebo to others with the following link: seebo.com/introducing-seebo.

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Our solutions address the burning need for factories and plants to cut downtime, boost production yield, and minimize product faults.

Powered by the Seebo IoT development platform, Seebo solutions are easily customized using visual, code-free tools for IoT Modeling, Simulation, Predictive Analytics, and Machine Learning. The result: unmatched speed-to-market and predictable ROI.

The Seebo IoT Development Platform is comprised of visual tools that enable quick configuration and customization of our business solutions:

IoT Modeler - Visualizes the solution blueprint, with the necessary technology layers and data flows, as well as the business use cases to be implemented

IoT Simulator - Quickly validates the solution blueprint and enables you to gain stakeholder buy-in

Predictive Analytics & Machine Learning - Automatically translates the business use cases to rule-driven alerts, and provides an iterative means to automatically learn from historical data, perform root-cause analysis, and derive actionable insights

Digital Twin dashboards - visualizes the KPIs, alerts, and reports in the context of your production lines, enabling you to drill in through your sites, machines, and sensors to drive your operations to excellence

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Manufacturers across industries – including Grundfos, Stanley, Procter & Gamble, Ralph Lauren, and many more – use Seebo to increase overall equipment effectiveness (OEE), minimize maintenance costs, and continually improve quality.

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Seebo’s IoT Snapshot maps the range and focus areas of Seebo’s IoT business across Technologies, Use Cases, Industries, and Services. Only categories with active products will be shown. Missing categories indicate that there is no activity in those areas.
Technologies
Platform as a Service (PaaS)
Data Management Platforms
Analytics & Modeling
Predictive Analytics
Use Cases
Digital Twin
Machine Condition Monitoring
Predictive Maintenance
Process Control & Optimization
Industries
Automotive
Chemicals
Food & Beverage
Metals
Oil & Gas
Pharmaceuticals
Seebo’s Tech Stack maps Seebo’s participation in the IoT tech stack.
  • Application Layer
  • Functional Applications

  • Cloud Layer
  • Platform as a Service
    Infrastructure as a Service

  • Edge Layer
  • Automation & Control
    Processors & Edge Intelligence
    Actuators
    Sensors

  • Devices Layer
  • Robots
    Drones
    Wearables
  • Supporting
    Technologies
  • Analytics & Modeling
    Application Infrastructure & Middleware
    Cybersecurity & Privacy
    Networks & Connectivity
Technological Capability
None
Minor
Moderate
Strong
Number of Case Studies3
Oseco Case Study - Delivering Condition Monitoring with Seebo
Oseco Case Study - Delivering Condition Monitoring with Seebo
Oseco were completely new to Industry 4.0, Oseco needed to find a lean and quick method for successfully implementing condition monitoring.
Seebo and Greengage Revolutionize Industrial Lighting System
Seebo and Greengage Revolutionize Industrial Lighting System
Greengage was looking for a way to provide ‘smart’ lighting solutions, to provide farmers with an essential system for managing operations and to monitor animal welfare remotely.
Reducing Downtime with Predictive Analytics
To improve production capacity and avoid downtime, a global biotechnology manufacturing company implemented Seebo Predictive Analytics.The company’s quarterly operations review revealed a 3.6% increase in downtime during production. This downtime stemmed from an unexplained viscosity in one product in the production line.The resulting pipeline blockages between the reactor and the centrifuge in the production line led to more frequent equipment cleaning procedures and stoppage during the batch production, high levels of waste, a decreased capacity, and lengthened time to market.The investigative team could not identify a reason for the blockage, as all relevant production parameters were in the approved working range.
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