Deepomatic has raised $10 million in a funding round. The startup has been able to convince some large-scale clients to use its platform. Telecom companies use Deepomatic to make sure that tasks have been completed successfully.
Deepomatic closed in October and is leading the new funding round. The existing investors are participating in a new round.
I first wrote about the startup in 2015, and it has been around for a few years now. Deep learning is the focus of the company. It has taken a long time to find clients for this technology.
Deepomatic has unlocked its true potential with the telecom industry. Augustin Marty told me that they found an industry that needed what they were working on.
When installing optical fiber cables or rolling out a new 5G tower, field workers have to fill out complicated forms to make sure they follow certain procedures. It can be difficult to work for contractors. Multiple telecom companies can work with those companies.
When you fill out a form, it is easy to make a mistake. Field workers can sometimes say that something is working well. There have been issues with fiber concentration points.
Many field service companies are using photos. They need to take a photo of their installation and their instruments to prove that the equipment is up and running. More work is what it means.
Photos are used by field service companies. The photos are analyzed to find out more. If something doesn't feel right, Deepomatic can send an alert.
Identifying mistakes is the most complex part of the process. Deepomatic now sells an end-to-end platform so that field workers only have to use Deepomatic. Specific enterprise tools are integrated with it.
Deepomatic works perfectly when the startup works with a new client. Adding control points, using existing tasks in its computer vision library or training its algorithm on a new set of photos are some of the things it entails. The startup's own infrastructure is used to train deepomatics. It can run on the client's own cloud infrastructure in some instances.
The company has a number of large accounts, as well as a number of smaller ones. Clients pay a lot of money to use Deepomatic.
More than one million on field operations are monitored by Deepomatic every month. More than 20,000 field workers take photos with their phones and send them to a Deepomatic back end.
Deepomatic would like to work with companies in Europe, the U.S. and South America.
The next few decades will see a lot of investment in infrastructure by governments and large companies. There is a shortage of talent. Deepomatic appears to be arriving at the right time on the market to become an essential tool for this infrastructure upgrade.
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