Let's talk
Let's talk

Our technology

We could have simply built a product, but we needed an ecosystem.

A male production techincian assembles pieces of the XperCount lid
Overview of XpertSea's ecosystem

IoT platform

Measurement technologies are the future of emerging industries, and we are proud to be spearheading that revolution in the aquaculture space.

At the core of our IoT platform is the Acquisition server, a daemon develop and optimized in C++. Interfacing high precision sensors through drivers and libraries, this server contains an embedded computer vision module that can run complex machine learning models. It exposes an API using websockets which can be used to control the device, locally or remotely.

Our devices are powered by Android and we leverage several out-of-the-box functionalities. This means we support most modern communications protocols and are able to push over-the-air updates.

XpertSea's IoT platform

Data platform

We're building the foundation of the first and largest aquaculture data source, a technological powerhouse that can be put to work to solve big problems.

Chart explaining XpertSea's data platform

We designed our data platform to be efficient, robust, maintainable and reusable. Developed in Python, it’s 100% cloud-based, powered entirely by AWS, and built to scale.

Using AWS managed services, we built a skeleton for data pipelines. This frame can be replicated into as many environments as we desire, and pipeline processors can be adjusted to any needs.

Our APIs are hosted on API Gateway and use Lambda's serverless infrastructure to provide infinite and easy scaling at a fraction of a normal API server cost.

SaaS platform

The SaaS platform is our customer-facing solution. A place to monitor daily information, and catch a glimpse of the future.

Our Software-as-a-Service platform is composed of every client, web app and tool that consumes data from the Data platform. This includes mobile applications developed for Android and our state-of-the-art Google Polymer 2.0 web application using Web Components. Polymer's awesome functionalities include offline access, precaching of elements, server push, HTTP/2, and much more.

The Cloudfront Content Delivery Network serves up our web app, which retrieves its data from our serverless APIs on AWS. Advanced analytics dashboards are forwarded from our business intelligences software to end users.

Chart explaining XpertSea's SaaS platform

Machine learning

Machine learning is a powerful but complex beast. It can be overwhelming at times. We try to automate the boring parts and concentrate on building value.

Chart explaining XpertSea's Machine Learning process

From classifying an aquatic animal to predicting the growth rate of a population, complex problems sometimes call for complex solutions. Hence, machine learning is at the core of our products.

We use different kinds of machine learning algorithms, from simple linear classifiers to recursive convolutional neural networks. All the model training and validation is done on the cloud.

We leverage AWS as an infinite source of power and use frameworks like OpenCV, Scikit Learn, Tensorflow and Keras. Our training framework can distribute and parallelize jobs on AWS EC2 clusters.


We see DevOps as a process of continuous improvement. Every minute invested has a compounding impact. The more you put in, the more you get out.

Chart explaining how XpertSea uses DevOps

We started containerizing all our projects early on, utilizing Docker to abstract environment from execution. Most of us use Linux, but some use MacOS or even Windows. With Docker, code always behaves the same, no matter where you run it.

Everything we do is cloud-based. Whenever a developer pushes new code with git, a webhook triggers our CI. It builds the code, if needed, and runs the tests. If everything passes, it deploys the binaries to S3 or the new Docker image to DockerHub. Otherwise, an alert is sent to the appropriate Slack channel.

Online services are deployed automatically by CloudFormation scripts which create all the AWS resources needed by the environment and fire up the machines.

All this, with a simple 'git push'.

Help us build the aquaculture intelligence platform of the future.

Line waves