Enterprise Data Science and ML Solutions
Appsilon provides innovative data analytics, machine learning, and managed services solutions for Fortune 500 companies and NGOs. We deliver the world’s most advanced R Shiny applications, with a unique ability to rapidly develop and scale enterprise Shiny dashboards. Our proprietary machine learning frameworks allow us to deliver Computer Vision, NLP, and fraud detection prototypes in as little as one week.
Above all, we are committed to making a positive impact on the world. Through our AI For Good Initiative, we routinely contribute our skills to projects that support the preservation of human life and the conservation of animal populations all over the globe. Recently, our team has worked to mitigate poaching in Africa with computer vision, provide satellite image analysis for assessing damage after natural disasters, and build tools to help with COVID-19 risk assessment. Appsilon is also a pioneer in open source. Our packages are actively used by global organizations such as Ubisoft, Bank of America, and Renault.
Appsilon is a proud RStudio Full Service Certified Partner.
Focus
Portfolio
BCG, Index Ventures, Diversey, Canadian Forest Service, Triple A Risk Finance, Black Red White, and Fortune 500 Companies across the globe
R Shiny Port Analytics Application
We created an attractive and user-friendly decision support system based on R Shiny that uses Automatic Identification System (AIS).
AIS is a real time system reporting position, speed, direction and other properties of vessels worldwide.
ML Image Classification to Analyze Wildlife Camera Trap Datasets
We worked with biodiversity conservationists at the National Parks Agency in Gabon in collaboration with experts from the University of Stirling to build an ML model that automatically identifies wildlife from camera trap images. We completed a fully functional Computer Vision ML model in two weeks. Our model was able to identify animals in images that human auditors frequently missed. Our model can quickly and accurately process millions of camera trap images, saving thousands of human work hours. We received additional support for this project from the Google for Education fund.
Learn more about the project here.
- ML Model to Identify Wildlife
- Significantly More Accurate Than Human Auditors
- Part of our AI For Good Initiative
AI for Assisting Natural Disaster Recovery
The Appsilon Data Science Machine Learning team recently took part in the xView2 competition organized by the Defense Innovation Unit (United States Department of Defense). Participants set out to utilize satellite imagery data to assist humanitarian efforts during natural disasters.
We were asked to build ML models using the novel xBD dataset provided by the organizers to estimate damage to infrastructure with the goal of reducing the amount of human labour and time required to plan an appropriate response.
Read more about the project here.
Interact with a demo of the final app here.
- ML Models to Assess Structural Damage
- Utilizes Satellite Image Datasets
- Part of our AI For Good Initiative
R Shiny Natural Language Processing App
We collaborated with the London School of Economics to create an intuitive R Shiny application that allows scientists and linguists to perform Natural Language Processing without the need for programming skills. The application is based on the R package Quanteda.
The app is commercially available to use here.
Computer Vision Defect Detection
We were approached by a major manufacturer to build a Machine Learning model for automatically detecting defects in cast iron products. We were able to train a working model and package it within an app for using the model as a prototype within two working days.
We used fast.ai on PyTorch (kaggle and GCP) for training the model. The app was built in Starlette.
- 99.6% Test Accuracy for Identifying Defects
- Two Days From Concept to Working Prototype
- Reliable Solution for Quality Control
Reviews
the project
Clustering Data Analysis for Data Analytics Platform
"We were impressed with the professionalism of the team and their project management style."
the reviewer
the review
The client submitted this review online.
Please describe your company and your position there.
I am the company CEO.
For what projects/services did your company hire Appsilon Data Science?
Our work involved complex clustering analysis of geospatial and time-series data.
What were your goals for this project?
We wanted to identify specific trends within our geospatial and time-series data.
How did you select Appsilon Data Science?
We have been aware of Appsilon's data science expertise for several years, so they were the natural choice when we required a partner to support a specific data analytics challenge.
Describe the project in detail.
We require specific trends to be identified from the large set of geospatial and time-series data.
What was the team composition?
The team was composed of a lead scientist and a support data scientist.
Can you share any outcomes from the project that demonstrate progress or success?
Appsilon exceeded our expectations. We would certainly work with them again on future projects.
How effective was the workflow between your team and theirs?
We were impressed with the professionalism of the team and their project management style.
What did you find most impressive about this company?
The consultants quickly grasped the complexity of the challenge, and were able to deliver an innovative solution.
Are there any areas for improvement?
No.
Appsilon Data Science exceeded the client's expectations and can be expected to be brought on for future projects. Their consultants quickly grasped the challenge and delivered an innovative solution.