Active

Global energy company seeking computer vision startups

Deadline: November 26, 2020

Eni, a global energy company, is looking for startups active in the field of computer vision, focusing in particular on industrial assets (upstream, refineries, chemical).

Currently, we have a number of active machine learning projects targeting our plants: from energy efficiency to production optimization, from anomaly detection on static and rotating equipment to HSE events monitoring and risk modelling. We also experimented briefly on vehicle tracking and safety equipment (helmet) detection via CCTV.

Now, we would like to explore how intelligent vision algorithms can boost our ability to understand the context, monitor multiple spots in our assets and detect in real time anomalies and unexpected events in general. We are interested in solutions for safety (both of staff and equipment), operations optimization and environmental impact monitoring.

Solution requirements:

  • We are open to both SW-only and HW-SW solutions, even though we have a slight preference for the former as it eases the deployment and adoption process;
  • We are open to solutions that require different types of input images in terms of size, granularity, frequency;
  • We are open to plug-and-play solutions that specialize in a specific task, but we are also open to companies that develop solutions for a specific need. However, we have a preference for companies that already have enough data to kick-start the training process;
  • We are also interested in general CV solutions, such as those that provide access to a wide range of datasets or CV platforms for labelling, annotation, multi-model training and inference and deployment.
Deadline: November 26, 2020
Posted on: October 26, 2020
Location: E-meeting (WebEx, Skype, Zoom, etc.)

Eni, a global energy company, is looking for startups active in the field of computer vision, focusing in particular on industrial assets (upstream, refineries, chemical).

Currently, we have a number of active machine learning projects targeting our plants: from energy efficiency to production optimization, from anomaly detection on static and rotating equipment to HSE events monitoring and risk modelling. We also experimented briefly on vehicle tracking and safety equipment (helmet) detection via CCTV.

Now, we would like to explore how intelligent vision algorithms can boost our ability to understand the context, monitor multiple spots in our assets and detect in real time anomalies and unexpected events in general. We are interested in solutions for safety (both of staff and equipment), operations optimization and environmental impact monitoring.

Solution requirements:

  • We are open to both SW-only and HW-SW solutions, even though we have a slight preference for the former as it eases the deployment and adoption process;
  • We are open to solutions that require different types of input images in terms of size, granularity, frequency;
  • We are open to plug-and-play solutions that specialize in a specific task, but we are also open to companies that develop solutions for a specific need. However, we have a preference for companies that already have enough data to kick-start the training process;
  • We are also interested in general CV solutions, such as those that provide access to a wide range of datasets or CV platforms for labelling, annotation, multi-model training and inference and deployment.

Application Requirements

In your response, please

  • Concisely what you offer & your match with the company above and their interest
  • Any relevant cases / customer stories (can indicate industry/size if not ready to go public)
  • Application Requirements

    In your response, please

    • Concisely what you offer & your match with the company above and their interest
    • Any relevant cases / customer stories (can indicate industry/size if not ready to go public)

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