Employee Highlight: Jorge Jara Featured for Pioneering AI Project with Amazon

At Eskuad, we love to see our talented team making headlines for the real-world innovation they’re driving every day. Recently, our own Jorge Jara, part of Eskuad’s development team, was featured in the Chilean outlets Revista Logistec and Ecosistema Startup for his work on a new AI initiative that’s taking shape from Laja, Chile — all in collaboration with Amazon Web Services (AWS).

As both articles highlight, this unique project brings together AI, practical field operations, and the global scale of port logistics — with a clear mission: solve real bottlenecks that slow down cargo movement and data capture in ports.

Bringing Generative AI to Port Operations

In the news, you’ll see how the project aims to streamline the recognition of shipping container codes, a deceptively simple task for humans — but surprisingly difficult for traditional computer systems operating in rugged port conditions.

Instead of building a complex system from scratch, Jorge and the team tapped into AWS’s Bedrock generative AI service, which uses large language models (LLMs) to interpret images on demand — a smart shortcut that saves both time and cost.

In Revista Logistec, they noted how this collaboration is part of Eskuad’s vision to push the boundaries of what’s possible for teams working in the field — even in ports that struggle with connectivity or complex logistics.

We Had to Ask Jorge…

To go deeper than the headlines, we caught up with Jorge to hear what the experience has been like behind the scenes — and what he’s learned so far.

On how this collaboration with Amazon began

“Most of it was about technical questions around implementing the shipping container code recognition. Our first idea was to build our own machine learning model with Amazon SageMaker, but that would’ve required a lot more work — finding the dataset, training, testing. AWS suggested using Amazon Bedrock, their generative AI service. It’s basically an LLM (like ChatGPT) that reads the image plus some instructions, then gives us back the code. This proved to be much simpler for our prototype, although it does need an internet connection.”

On what makes this approach stand out

“The fact that we can leverage AI for tasks that are simple for humans but tough for computers is definitely a plus. You just need to instruct the LLM properly. This saves a lot of time compared to a traditional OCR system — where you’d need perfect pictures and expensive training. t’s a great shortcut for companies that want to deploy something complex in a short time.”

On what it’s like to work with AWS

“AWS makes it easier because they provide all the services you might need — without having to buy or maintain expensive equipment. Plus, the people we’ve talked to at AWS have been super helpful. I didn’t expect to be speaking directly with an Amazon engineer! They gave us ideas, answered questions, and showed us what was possible with their tools.”

On the biggest challenge so far

“Definitely the prompting. These AI systems have improved a lot, but you still need to give them clear, explicit instructions — examples, edge cases, what to do if things go wrong (like when the image is too blurry or there’s no container at all). They’re not at the level of a human yet — they need context to output data in a structured way for other systems to use it.”

 A Small Team, Big Impact

This project is proof of how field innovation can start anywhere — even from Laja — and have global reach. Jorge’s practical, no-nonsense approach reflects what Eskuad is all about: helping real operations teams solve everyday problems with the best tools available.

 You can read more about this AI initiative in Revista Logistec or Ecosistema Startup.

We’re proud to have Jorge on the team — and excited to see what’s next for this AI-powered vision for port logistics.