Machine Learning provides smart alternatives for analyzing vast volumes of data. From anomalies detection, through demands prediction, to complex object classification, Machine Learning uses statistics to automate and optimize daily routines.
We have ML and DataScience specialists with experience in deploying custom solutions for small and large-scale projects. Our solutions are always optimized for your specific use-case.
Years of experience
A modern, fast and vast ecosystem for developing robust ML algorithms. With TFX pipelines we can automate the whole ML deployment process for production environments. Our Tensorflow developers are certified.
An API for Deep Learning development. Our code for Deep Neural Networks is understandable and extendable for any ML Engineer.
ML algorithms library. We use and extend well tested and most efficient ML algorithms.
ML explainers. We can explain and visualize how our ML models work even to non-technical users.
“We were an early-stage startup that had an idea, and working with Profil, we were able to get an MVP launch quickly. The expertise of the team is phenomenal - depth of knowledge on backend development, and rapid iteration on frontend work. We have been working with Profil for over 2 and a half years now and will continue to do so into the future.”
“The collaboration with Profil Software has permitted key in-house staff to work on company management, freeing up their time and ensuring deliverables are produced much quicker. They are a fantastic team, with excellent skills, effective methodologies, and good suggestions.”
“…Profil Software picked up our processes quickly.
They’re willing to learn new things and offer great insights.
The solutions improve the client’s speed and accuracy of performing tasks, and a new form of testing ensures fewer bugs, better uptime, and happier customers.”
Jog.ai provides recordings and accurate transcriptions for the phone and conference calls. The overall goal is to allow people to have meaningful conversations and have not their attention drawn away from the call by the need of taking notes.
3 practical examples for tricking Neural Networks using GA and FGSM. How can object classification be easily fooled?