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DISRUPTIVE AI TECHNOLOGIES

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AI ROADMAP

  • Identifying initiatives of true value. Filtering Hype. 

  • Bringing focus to Industry specific Disruptive Use-Cases.

  • Managing the iterative nature of AI Initiatives.

  • Defining Data Strategy which is very important for AI initiatives success.

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MANUFACTURING FOCUS

  • Machinery Preventive Maintenance. Optimizing Frequency and Operations.  

  • Quality / Visual Inspection. 

  • Increasing Production efficiency, removing bottlenecks. Optimization.

  • Improved Sales Forecast, Lead Qualification.

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MACHINE LEARNING

  • Good understanding & delivery capability in various Machine learning aspects.

  • Supervised, Unsupervised & Reinforcement Models.

  • Classifications, Training Models, SVM, Decision Trees, Ensemble Learning.

  • Deep Learning  & Artificial Neural Network Algorithms.

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CLOUD & EDGE AI

CLOUD

  • Handling movement of data to cloud and Maintenance.

  • Managing Cost, Performance, Work Load and Data Access.

EDGE

  • Real-time Sensor Data Analytics & IOT.

  • Handling Scalability, Power Consumption & Latency.