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Build a video insights and summarization engine using generative AI with Amazon Bedrock

AWS Machine Learning

This post presents a solution where you can upload a recording of your meeting (a feature available in most modern digital communication services such as Amazon Chime ) to a centralized video insights and summarization engine. This post provides guidance on how you can create a video insights and summarization engine using AWS AI/ML services.

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How to scale machine learning inference for multi-tenant SaaS use cases

AWS Machine Learning

Staff Machine Learning Engineer at Zendesk. Zendesk is a SaaS company that builds support, sales, and customer engagement software for everyone, with simplicity as the foundation. Customers like Zendesk have built successful, high-scale software as a service (SaaS) businesses on Amazon Web Services (AWS).

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Seven things B2B SaaS customer teams can learn from consumer subscription businesses

ChurnZero

You might be surprised to know that SaaS companies can learn a lot from their consumer subscription counterparts. The differences between SaaS and B2C companies. 2: Payment structure SaaS is paid on a recurring basis. But most SaaS organizations still have the luxury of long-term (2+ year) contracts.

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Don’t Make These Frequent Freemium SaaS Mistakes

Totango

A freemium strategy is one of the best ways to sell a SaaS product. However, common freemium SaaS mistakes can thwart this otherwise effective approach. Here we’ll help you steer clear of the most frequent pitfalls SaaS companies encounter when deploying a freemium sales model. Limiting storage space. Limiting customer support.

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Transforming credit decisions using generative AI with Rich Data Co and AWS

AWS Machine Learning

Its software-as-a-service (SaaS) solution empowers leading banks and lenders with deep customer insights and AI-driven decision-making capabilities. Our initial approach combined prompt engineering and traditional Retrieval Augmented Generation (RAG).

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How Vericast optimized feature engineering using Amazon SageMaker Processing

AWS Machine Learning

One aspect of this data preparation is feature engineering. Feature engineering refers to the process where relevant variables are identified, selected, and manipulated to transform the raw data into more useful and usable forms for use with the ML algorithm used to train a model and perform inference against it.

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Cloud Based Solutions, the Contact Center and Future of AI

CCNG

So in a world where every product description ends in “aaS” from SaaS to CCaaS, it only makes sense that AI should follow suit. In the same way it’s a faux pas for engineers to test their new software in production, it’s just as ill advised to train an AI in the wild with actual customers who need their issues solved.