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

AWS Machine Learning

Furthermore, these notes are usually personal and not stored in a central location, which is a lost opportunity for businesses to learn what does and doesn’t work, as well as how to improve their sales, purchasing, and communication processes. Many commercial generative AI solutions available are expensive and require user-based licenses.

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20 Call Center Pros Share the Most Undervalued Call Center Metrics and How To Better Leverage Them

Callminer

From essentials like average handle time to broader metrics such as call center service levels , there are dozens of metrics that call center leaders and QA teams must stay on top of, and they all provide visibility into some aspect of performance. Kaye Chapman @kayejchapman. First contact resolution (FCR) measures might be…”.

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Build a reverse image search engine with Amazon Titan Multimodal Embeddings in Amazon Bedrock and AWS managed services

AWS Machine Learning

A reverse image search engine enables users to upload an image to find related information instead of using text-based queries. With Amazon Titan Multimodal Embeddings , you can power more accurate and contextually relevant multimodal search, recommendation, and personalization experiences for users. Engine : Select nmslib.

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Few-shot prompt engineering and fine-tuning for LLMs in Amazon Bedrock

AWS Machine Learning

Investors and analysts closely watch key metrics like revenue growth, earnings per share, margins, cash flow, and projections to assess performance against peers and industry trends. Model customization helps you deliver differentiated and personalized user experiences.

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The Challenges of Omnichannel: Why so Many Contact Centers Struggle with Digital Self-Service

To find how contact centers are navigating the transition to omnichannel customer service, Calabrio surveyed more than 1,000 marketing and customer experience leaders in the U.S. about their digital customer communication strategies. Read the report to find out what was uncovered.

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AI-Driven Customer Service Demands Humanized CX

TechSee

Check out how Sophie AI’s cognitive engine orchestrates smart interactions using a multi-layered approach to AI reasoning. Support becomes more personal. Reducing Churn : Personalized experiences make customers feel valued, boosting loyalty and retention. ” Curious how it works? Ready to Transform Your CX?

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Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning

The DS uses SageMaker Training jobs to generate metrics captured by , selects a candidate model, and registers the model version inside the shared model group in their local model registry. Optionally, this model group can also be shared with their test and production accounts if local account access to model versions is needed.