I’m Nelson and I’ve been a Software Engineer at Jungle for almost 5 years now. From intern, to Software Engineer, to team lead: here's my journey so far.  

Our main product, Canopy, is built on top of very advanced AI models that are agnostic to the application. This means that they can be used to reduce machine downtime in various industries.

Today we will go on a journey to discover some of the key advantages our Time-Machine AI models bring to predictive maintenance pipelines. They helped us solve some of the biggest challenges we have encountered on our way, so hold on to your seats!

The need for AI-based predictive solutions for electromechanical assets is on the rise. However, building large scale AI-dependent online systems is by no means an easy feat. Successfully creating useful prediction analytics pipelines requires experience and some of the big challenges are only uncovered once a solution is used during daily operations!

A very commonly heard thing about AI models is that the more data available the better. This is only the case if the model is actually able to leverage all the data. More often than not this is, unfortunately, not the case. One of the main reasons is data quality, and sensor availability specifically.

We came down to four big topics: being outside & exercising, eating, communicating, and (not) commuting.

The wind energy industry event will take place virtually between the 23rd and the 24th of February.

Lisbon & Amsterdam, May 2021 – Dutch artificial intelligence company Jungle raises funding of 1 million euro from impact investor SHIFT Invest. The capital raised completes Jungle’s 3.2 million euro seed stage funding. It will be used to accelerate the development of Jungle’s AI platform Canopy, and its deployment in renewable energy and industrial processes.

Discover six different ways our product helps wind portfolio owners increase their profitability.

Amsterdam, 29 April 2024 – Dutch companies Jungle AI and MO4 have partnered up to increase efficiency in the offshore sector by minimising vessel downtime. This partnership has allowed the two companies to combine their groundbreaking technologies to increase uptime and profitability in the maritime sector.

Jungle AI and MO4 have joined forces to enhance efficiency and minimise both mechanical and weather downtime in the maritime sector.

The wind energy industry event will take place in Berlin, on March 7-8.

The latest additions to the Canopy portfolio are two wind farms in the Nordics, Kalax and Sørfjord, which are operated by European energy company Fortum.

This month, Jungle turned 5. During our journey of starting a deep-tech company in the Machine Learning space, we’ve grown as individuals and as a team, and learned many lessons. Today we’ll share the 5 most important ones with you.

Amsterdam & Lisbon, 5 September 2022 – Jungle, a Dutch artificial intelligence company, has closed a 5 million euro Series A funding round led by SHIFT Invest, complemented by Rocks International Group, EDP Ventures, Gorilla Growth Capital and Future Energy Ventures. This funding allows the company to accelerate the deployment of its technology in the renewable energy and industrial sectors.

The wind energy industry event will take place virtually between the 23rd and the 24th of February.

Lisbon & Amsterdam, May 2021 – Dutch artificial intelligence company Jungle raises funding of 1 million euro from impact investor SHIFT Invest. The capital raised completes Jungle’s 3.2 million euro seed stage funding. It will be used to accelerate the development of Jungle’s AI platform Canopy, and its deployment in renewable energy and industrial processes.

Jungle’s CIO & co-founder Silvio Rodrigues shares the thoughts and technology behind Detections and the difference it makes in everyday renewables operations.

Renewable energy power forecasting represents one of Jungle’s solutions that accelerate our mission to develop the world’s most effective tools to resolve underperformance stemming from operational complexity.

Our main product, Canopy, is built on top of very advanced AI models that are agnostic to the application. This means that they can be used to reduce machine downtime in various industries.

Today we will go on a journey to discover some of the key advantages our Time-Machine AI models bring to predictive maintenance pipelines. They helped us solve some of the biggest challenges we have encountered on our way, so hold on to your seats!

The need for AI-based predictive solutions for electromechanical assets is on the rise. However, building large scale AI-dependent online systems is by no means an easy feat. Successfully creating useful prediction analytics pipelines requires experience and some of the big challenges are only uncovered once a solution is used during daily operations!

A very commonly heard thing about AI models is that the more data available the better. This is only the case if the model is actually able to leverage all the data. More often than not this is, unfortunately, not the case. One of the main reasons is data quality, and sensor availability specifically.

Discover six different ways our product helps wind portfolio owners increase their profitability.

Component overheating impacts wind portfolio revenues. Discover how to detect and minimise its impact on your fleet.

In this blog post, we present why SCADA alarms are abundant but not helpful for operators.

Unravel the experience of a technical expert visiting one of the biggest renewables industry events for the first time.

Last year, Jerónimo Mendes joined Jungle for a summer internship. Fast forward to the present and he’s officially one of Jungle’s software developers!

I’m Nelson and I’ve been a Software Engineer at Jungle for almost 5 years now. From intern, to Software Engineer, to team lead: here's my journey so far.  

We came down to four big topics: being outside & exercising, eating, communicating, and (not) commuting.