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How AWS Sales uses generative AI to streamline account planning

AWS Machine Learning

These documents are internally called account plans (APs). In 2024, this activity took an account manager (AM) up to 40 hours per customer. In this post, we showcase how the AWS Sales product team built the generative AI account plans draft assistant.

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Getting started with computer use in Amazon Bedrock Agents

AWS Machine Learning

Traditional automation approaches require custom API integrations for each application, creating significant development overhead. Add the Amazon Bedrock Agents supported computer use action groups to your agent using CreateAgentActionGroup API. Finally, the CRM agent was used to get additional information on the customer.

APIs 135
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How AWS sales uses Amazon Q Business for customer engagement

AWS Machine Learning

Since that time, thousands of active users have asked hundreds of thousands of questions through Field Advisor, which we have embedded in our customer relationship management (CRM) system, as well as through a Slack application. The following screenshot shows an example of an interaction with Field Advisor.

Sales 110
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From innovation to impact: How AWS and NVIDIA enable real-world generative AI success

AWS Machine Learning

They use a highly optimized inference stack built with NVIDIA TensorRT-LLM and NVIDIA Triton Inference Server to serve both their search application and pplx-api, their public API service that gives developers access to their proprietary models. The results speak for themselvestheir inference stack achieves up to 3.1

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Get more out of SuccessBLOCS and APIs

Totango

Totango has now enabled write-back functionality so information flows from Totango back to your source systems like your CRM or Customer Support Platform. Stream Account & User Tag Information Using Customer Data Hub API. Now, tag information can be easily streamed to Totango via Customer Data Hub API.

APIs 62
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Accelerate client success management through email classification with Hugging Face on Amazon SageMaker

AWS Machine Learning

Solution overview Scalable Capital’s ML infrastructure consists of two AWS accounts: one as an environment for the development stage and the other one for the production stage. The function then relays the classification back to CRM through the API Gateway public endpoint.

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The Essential Guide to WFM – Key Features to Look For

CCNG

Forecasting Core Features The Ability to Consume Historical Data Whether it’s from a copy/paste of a spreadsheet or an API connection, your WFM platform must have the ability to consume historical data. If your platform produces amazing forecasts but no aligned schedules, then you likely have a data analytics platform and not a WFM platform.