AI for High Tech

AI enables companies to continuously learn how they can improve processes, enhance partnerships and gauge market forces. Businesses in the high-tech industry are leveraging AI to reshape the core functions

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MLOps and AIOps

Businesses are investing in their data science teams and ML capabilities to develop predictive models that can deliver business value to their users.

Explainable MLOps

 ML engineering culture and practice that aims at unifying ML system development (Dev) and ML system operation (Ops). Practicing MLOps means that you advocate for automation and monitoring at all steps of ML system construction, including integration, testing, releasing, deployment and infrastructure management.

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MLOps

The challenge is building an integrated ML system and to continuously operate it in production

AIOps

AI in IT Operations reshapes three core functions

Accelerated AIOps

By integrating AI-supported deep learning and analytics with product development and other processes, companies can effectively predict which directions they should next turn, create products faster than before and continuously improve how they operate.
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Conversational AI

Enable rich and conversational experiences with AI-powered features

Foster relationships, not just transactions

Gives customers 24/7 access to immediate conversational self-service, with seamless handoffs to human agents for more complex issues.

Increase operational efficiency

Empowers human agents with continuous support during their calls and chats by identifying intent and providing real-time, step-by-step assistance.

Turn every agent into a specialist

Free human agents to focus on more difficult and specialized calls, providing them with real-time information, workflows, and turn-by-turn guidance.

DeepBrainz Assistant for Conversational AI

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We’re working on delivering our products’ services, and solutions to everyone including the enterprises.

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