VMLpro facilitates the collation, curation, collaboration and computation of extremely large EEG data sets from anywhere at anytime.

Rapid, parallel processing advances research through high-performance cloud computing, scalable across thousands of cores, increasing throughput and accelerating discovery.

By taking advantage of scalable, massively parallel cloud computing delivered as software as a service (SaaS), VMLpro allows users to take their analyses (kBs) to their data (TBs) and then distributes the results, in real-time, to their network of collaborators without the barriers of institutional firewalls.

EEG recordings, metadata and analysis routines (plug-ins) are uploaded to the cloud. Sensitive patient data are encrypted and stored independently of anonymised data and linked via a unique encrypted key to ensure data security.

Storage capacity and processing nodes are scaled automatically to meet current requirements thus optimising the user’s computing needs in real-time, avoiding redundancies in data duplication and ensuring users have persistent access to data, and the most recent versions of analytics.

The technology

Platform infrastructure

  • Latest technologies from Amazon Web Services (AWS)
  • Decoupled and distributed: no single point of failure
  • Load balancing to handle growing users / databases
  • Disposable analysis servers (Spark on EC2)
  • On demand platform scaling
  • Improved cost efficiency
  • EDF, HDF5 and NXE data formats supported
  • JSON / REST API supports Android, iOS and web clients

Batch and real time analysis

  • Supervised and unsupervised machine learning algorithms
  • Run R, Python, Scala and Java code in the same cluster


  • SSL communication between clients and servers
  • Encrypted user repository (at rest and in transit)
  • Multi-tenant access privileges
  • Fully audited API calls
  • AWS firewalls protect database and analysis servers
  • Multi-factor authentication


  • Centralised error logs via Papertrail
  • Help desk for bugs, issues and requests within 24 hours

Partner with us

If you are interested in using VMLpro in your own research or in the development of other applications, please get in touch.

Customer Feedback

Professor Chris Toumazou
Chief Scientist, Institute of Biomedical Engineering,
Imperial College, London

"This sort of technology is pushing us out of the lab....where we can interpret data very efficiently, very proactively."