Technology

User interface

Multi-channel platform (Mobile, Desktop, Web) with third party channel support (Slack, FB Messenger, etc.).

CUI framework

Hybrid UI: CUI + GUI combined with plug-in architecture (own plug-ins extending standard UI library).

Machine learning

Learn from data and user context – you decide what user context features should be learned (location type, calendar events, in-call situations, driving car, etc).

Data integration

Use our app with your data and your custom messages or embed our platform in your app (it’s as simple as FireBase integration!)

Front-end mechanisms are composed of Hybrid CUI Platform (Android, iOS, Web, Desktop, third party channels e.g. Slack, Facebook Messenger), User and Company Context Builder and Intelligent Assistant apps (Android, iOS, Web, Desktop) based on Hybrid CUI Platform.

Our back-end technology (data crunching, intelligence, administration) consist of Cloud User and Company Context Building Services, Professional Knowledge Building Services, Business Intelligence Services and Machine Learning

Platform.Back-end stack: Machine Learning frameworks (Python), Microservices / API (node.js), NoSQL (MongoDB), Graph Databases (Neo4j), Enterprise Service Bus (Mule ESB), Large scale data processing (Apache Spark), Message brokers (RabbitMQ)

Machine Learning frameworks: Machine Learning toolkit (scikit-learn), Boosted Decision Trees (xgboost), Neural Networks (TensorFlow)

Deep Neural Networks we use: Recurrent Neural Networks (RNN), Long Short-Term Memory neural networks (LSTM), Convolutional Neural Networks (CNN), One-shot Learning with Memory-Augmented Neural Networks (MANN), Ensemble of Neural Networks.

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