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[Interview] Quality Control Automation, in Real-Time

The future, blending digital and energy, promises to be rich in challenges. Between the necessary transition to advanced telecommunication infrastructures and the imperative of clean energy, stakeholders in these markets find themselves at a crossroads. In this context, Deepomatic claims to be ready to revolutionize these domains with its AI-based solution for automation of quality control.

Informations Entreprise: What is your vision of the current and future challenges in the telecom and energy sectors?

Augustin Marty (CEO of Deepomatic): These are sectors that employ tens of thousands of technicians who work daily in the field to build and maintain essential infrastructure. This includes fiber optic networks, 5G and 4G antennas, deployment of energy networks (water-gas-electricity), solar panels, and electric vehicle charging stations. These infrastructures are crucial to meeting societal imperatives of inclusion and internet access for individuals and businesses. They support the challenges of ecological transition and energy efficiency efforts, even addressing sovereignty issues.

However, we observe, in a context of accelerated deployment of all these infrastructures, a real crisis in quality, particularly notable in the fiber sector, but starting to affect other areas. This situation stems from a chronic lack of qualified manpower. These are manual jobs that attract few candidates, with employees reluctant to commit long-term to the company, resulting in a significant attrition rate.

In an increasingly competitive landscape with multiple Telecom operators, quality is at the heart of customer retention challenges. The ability to retain new subscribers by ensuring impeccable service quality is essential, as is the speed of connection, but not at the expense of quality. Repeated failures in field interventions can lead to the loss of potential subscribers even before billing for the first month.

Field workers installing fiber optic cables in a trench

I.E: How does Deepomatic use artificial intelligence technologies to address these challenges?

Augustin Marty: We are at a turning point where service quality directly impacts the financial performance of our clients. Our value proposition is to put quality back at the heart of field operations, relying on the use of artificial intelligence, or Computer Vision, to support technicians in the field by enabling them to perform their interventions right the first time with a high level of quality.

Through photo capture, Deepomatic analyzes the intervention in real-time and validates the compliance of the task or alerts the technician in case of non-compliance.

This approach aims to reconcile productivity and quality by automating quality control, thus ensuring a successful first customer experience and fostering long-term subscriber loyalty. It also guarantees for companies full visibility on the health of their infrastructures. They can organize maintenance operations in full knowledge and thus avoid costly re-interventions.

I.E: How important is intervention documentation to you?

Augustin Marty: It is essential to ensure that actions taken are rigorously documented. This requirement is crucial for two main reasons.

Firstly, precise and comprehensive documentation allows for a clear understanding of the operations performed, thereby facilitating future interventions. It is crucial to have photos and accurate references of installed or replaced equipment.

Secondly, beyond operational aspects, this documentation often meets unavoidable contractual obligations. Through a set of photographs shared at each stage of the process, this documentation facilitates the flow of information and reinforces the responsibility of the various actors involved. Finally, in an era where we operate in a complex subcontracting ecosystem, precise reporting helps to ensure the billing of operators and the payment of subcontractors by providing proof of the quality and compliance of the work performed.

Our clients, by adopting our solution, achieve an exact reporting rate of over 99%, demonstrating the effectiveness of our approach.

Technician taking a photo of a fiber distribution point and obtaining feedback from the AI-powered quality control solution

I.E: What are your development projects?

Augustin Marty: We will obviously continue to work alongside telecom operators to support them in their field challenges. However, the vision we carry today is more international and diversified, addressing a wider range of field services. These are demanding professions that require frequent travel to carry out various interventions. Technicians often face a variety of missions that require versatility to effectively intervene in several areas.

In our opinion, the key to this adaptability lies in the use of new technologies, particularly artificial intelligence, which offers powerful tools to support and guide technicians in the field, enabling them to be more efficient. Through real-time analysis of images captured during interventions, AI can correct errors instantly, thus ensuring the quality and safety of the work performed. This vision, embodied by our company, aims to provide workers with the necessary means to succeed in their missions, while effectively meeting demand in a context of scarcity of qualified labor.

That's why we are strengthening our ties with subcontractors and construction companies. Our goal is to become a strategic partner for these actors. We work in collaboration with them to identify new use cases for which our visual AI solution will provide an answer. The objective is to expand into new markets, both in France and internationally. This direction marks a significant step in Deepomatic's evolution.

Interview published in Informations Entreprise n°190 April, May, June 2024.

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