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Streamline Sales Processes with Enterprise CPQ

Cincom

Managing sales processes across large organizations is complex. From coordinating teams to configuring quotes, enterprise companies face immense challenges keeping sales operations running smoothly. This frustrates customers and limits sales capacity. Sales data gets scattered across systems. What Is CPQ Software?

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Jul 07 – Customer Success Jobs

SmartKarrot

Ensure their customers successfully deploy, adopt, and maintain Rapid7 solutions and continue to renew their licenses year-over-year. Build long-term relationships, drive adoption of their tools, generate referrals, identify upsell and cross-sell opportunities. Increase product adoption, customer engagement and satisfaction.

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Bring SageMaker Autopilot into your MLOps processes using a custom SageMaker Project

AWS Machine Learning

Amazon SageMaker is a fully managed service to prepare data and build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows. We demonstrate how to use CI/CD the low-code/no-code tools code to integrate it into your MLOps environment, while adhering with MLOps best practices.

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HCLTech’s AWS powered AutoWise Companion: A seamless experience for informed automotive buyer decisions with data-driven design

AWS Machine Learning

By tailoring recommendations based on individuals preferences, the solution guides customers toward the best vehicle model for them. Simultaneously, it empowers vehicle manufacturers (original equipment manufacturers (OEMs)) by using real customer feedback to drive strategic decisions, boosting sales and company profits.

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Amazon Bedrock Custom Model Import now generally available

AWS Machine Learning

Amazon Bedrock offers a serverless experience, so you can get started quickly, privately customize FMs with your own data, and integrate and deploy them into your applications using AWS tools without having to manage infrastructure. Be backed by enterprise grade security and privacy tooling. from sagemaker.s3

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