We help businesses identify opportunities, implement solutions according to data science best practices, and deploy solutions into production systems.
We collect data from any type of data store, build specific crawlers and web scrapers to fetch data, or interface with real-time data streams.
We use optimal tools and algorithms to prepare, clean, denoise, filter, format, deduplicate, augment, annotate and label data.
We extract features, train models to learn patterns from data and export predictions to any type of data store.
We provide relevant recommendations and insight through data visualisation, streamlining search, manipulation and analysis.
Cyanapse is a startup company specialised in data science. We focus on using and developing cutting-edge brain-inspired algorithms to address business data and provide customised solutions tailored to our clients’ needs.
Combining expert knowledge from Neuroscience, Machine Learning and Natural Language Processing, we deploy state-of-the-art data pipelines to provide insights and visualisations to help our clients master their data and become “Number 1” in their sector.
Cyanapse was established in 2016 by two computational neuroscientists who are passionate about turning unstructured data into meaningful insights. We have been working with a variety of clients worldwide, providing us with substantial and diverse experience in bespoke data science.
Our team of Data Scientits and Software Engineers is happy to investigate novel cases and new data. We perform in-depth data examination and provide our clients with detailed solutions that solve real-world data problems.
Co-Founder, Technology Executive
Sebastien completed a PhD in Computational Neuroscience. He developed cutting-edge mutual information analysis methods to process brain data. He has also worked on a number of data projects where he developed advanced data processing pipelines for unstructured text and HTML.
Co-Founder, Chief Scientist
Esin completed a PhD in Computational Neuroscience. She developed novel blind source separation analysis methods for imaging data. She also worked on a GPU-accelerated simulator and studied learning algorithms in biologically-realistic spiking neural networks.
Get in touch for a free meeting to discuss your case with us.