Leverage our experience in Machine and Deep learning models development, Big Data, and Cloud technology to successfully build, deploy, and manage AI solutions in your industry.
▸ Talk to Our ExpertsFull-cycle development of custom AI models based on Deep and Machine Learning algorithms, including Data Science research, training, validation, testing
Comprehensive infrastructure management for Machine Learning workloads
Architecture design and implementation for Enterprise Big Data solutions
Implementation of AI application lifecycle management and CI/CD
ML models customization for on-the-edge device deployment
Establish integration with AI-ready cloud platforms and third-party APIs
From careful project analysis and ideation stage — to solution roll-out and management, the experts of Intellectsoft AI Lab will help you every step of the way with your solution.
Data migration from legacy systems to new platform
Design data platform tailored to the business needs
Components implementation and deployment
Recommendation Engine
Analysis of domain and data
▸ All major ML frameworks
▸ Pre-built and pre-trained models for multiple vertical use-cases (prediction, classification, segmentation, anomaly detection, NLU)
▸ Design, deployment, and support of enterprise AI production workflow for on-prem DCs and public clouds
▸ Enterprise Big Data technology stack: SQL/NoSQL databases, ETL, ingestion, streaming analytics
▸ Cloud based ML platforms and services (Azure ML, AWS ML, Google AutoML, Clarifai, Watson)
▸ Accelerated compute infrastructure
Use your customer big data and let algorithms make tailored recommendations in retail. Establish a single data lake for your entire hotel chain. Create an advanced virtual assistant for your hospital.
Image recognitions systems that monitor unsafe worker behaviour, project schedule optimizers, algorithms that help prevent downtime, and more
Advanced virtual assistants, imagining diagnostics algorithms, predictive pandemics analytics, and other solutions
AI-driven claim process, advanced customer chatbots, personalization of customer experience, predictive analytics
Highly personalised customer journeys, algorithms that predict demand, automated inventory and delivery management
Personalised guest experience, virtual assistants, voice-activated services, smart on-premises alerts and offers
Smart traffic control, engine monitoring and predictive maintenance, semi-autonomous functionality
▸ System and customer data collection, processing and storage platform
▸ Data volume ingestion: 3T/day (1P/year)
▸ Data velocity ingestion: 50000 events per second
▸ Computational power increase by factor of x10 vs. Legacy systems
▸ Streamlined architecture for 5 legacy products and 7 brand new projects — implemented by a single team of 10 engineers
▸ Large data sets provide spot-on business insights
▸ Heterogeneous Infrastructure Topology (Hybrid Cloud) for security and efficiency
The client’s existing architecture and technology could not manage the enormous client growth that reached over 80 million TV clients as the system collapse was looming. The new Big Data platform prevented it and brought a wide array of impactful benefits:
▸ Single point for all data ingestion, processing, and distribution across all systems
▸ Batch and stream data processing allowed for designing Machine Learning and real time data-driven applications
▸ System’s inherent scalability increased data collection rate by factor of x100 to implement Recommendations, Fault, and churn prediction algorithms
▸ Fast events and activity feedback from millions of customers provided significantly increased the company’s revenue
▸ Large data sets provide spot-on insights for business decision making
▸ Replaced all databases and data silos
▸ AI and ML-driven applications paved the road to challenge competition from internet disruptors
▸ Personalized targeted Content Recommender
▸ Model based on historical viewership events and current activity
▸ Co-Occurrence, Collaborative Filtering and Binary Logistic Regression Evaluated algorithms
▸ Spark MLlib based learning and recommendation components
▸ Sophisticated Probabilistic User behavior simulator for improved model quality
▸ Multi-staged Architecture
▸ System and customer data collection, processing and storage platform
▸ Data volume ingestion: 3T/day (1P/year)
▸ Data velocity ingestion: 50000 events per second
▸ Computational power increase by factor of x10 vs. Legacy systems
▸ Streamlined architecture for 5 legacy products and 7 brand new projects — implemented by a single team of 10 engineers
▸ Large data sets provide spot-on business insights
▸ Heterogeneous Infrastructure Topology (Hybrid Cloud) for security and efficiency
The client’s existing architecture and technology could not manage the enormous client growth that reached over 80 million TV clients as the system collapse was looming. The new Big Data platform prevented it and brought a wide array of impactful benefits:
▸ Single point for all data ingestion, processing, and distribution across all systems
▸ Batch and stream data processing allowed for designing Machine Learning and real time data-driven applications
▸ System’s inherent scalability increased data collection rate by factor of x100 to implement Recommendations, Fault, and churn prediction algorithms
▸ Fast events and activity feedback from millions of customers provided significantly increased the company’s revenue
▸ Large data sets provide spot-on insights for business decision making
▸ Replaced all databases and data silos
▸ AI and ML-driven applications paved the road to challenge competition from internet disruptors
Thank you! We will get back to you within a few hours.
By sending this form I confirm that I have read and accept Intellectsoft Privacy Policy