AWS Machine Learning

NOVEMBER 20, 2024

By narrowing down the search space to the most relevant documents or chunks, metadata filtering reduces noise and irrelevant information, enabling the LLM to focus on the most relevant content. This approach narrows down the search space to the most relevant documents or passages, reducing noise and irrelevant information.

Construction 114

Construction APIs Metrics Accountability 114

AWS Machine Learning

SEPTEMBER 8, 2023

For modern companies that deal with enormous volumes of documents such as contracts, invoices, resumes, and reports, efficiently processing and retrieving pertinent data is critical to maintaining a competitive edge. What if there was a way to process documents intelligently and make them searchable in with high accuracy?

Construction 127

Construction Metrics Best practices APIs 127

AWS Machine Learning

JANUARY 28, 2025

By documenting the specific model versions, fine-tuning parameters, and prompt engineering techniques employed, teams can better understand the factors contributing to their AI systems performance. Evaluation algorithm Computes evaluation metrics to model outputs. Different algorithms have different metrics to be specified.

Management 100

Management APIs Engineering Metrics 100

AWS Machine Learning

JANUARY 7, 2025

The solution offers two TM retrieval modes for users to choose from: vector and document search. When using the Amazon OpenSearch Service adapter (document search), translation unit groupings are parsed and stored into an index dedicated to the uploaded file. This is covered in detail later in the post.

Engineering 104

Engineering Metrics industry standards Finance 104

AWS Machine Learning

JANUARY 8, 2024

AWS customers in healthcare, financial services, the public sector, and other industries store billions of documents as images or PDFs in Amazon Simple Storage Service (Amazon S3). In this post, we focus on processing a large collection of documents into raw text files and storing them in Amazon S3.

Scripts 107

Scripts Construction APIs Healthcare 107

AWS Machine Learning

FEBRUARY 7, 2024

In the first post of this three-part series, we presented a solution that demonstrates how you can automate detecting document tampering and fraud at scale using AWS AI and machine learning (ML) services for a mortgage underwriting use case. The following diagram represents each stage in a mortgage document fraud detection pipeline.

APIs 130

APIs Accountability Metrics Engineering 130

AWS Machine Learning

FEBRUARY 12, 2025

This approach allows organizations to assess their AI models effectiveness using pre-defined metrics, making sure that the technology aligns with their specific needs and objectives. Prerequisites To use the LLM-as-a-judge model evaluation, make sure that you have satisfied the following requirements: An active AWS account.

Metrics 91

Metrics Engineering Benchmark APIs 91

ProProfs Blog

APRIL 17, 2020

But without numbers or metric data in hand, coming up with any new strategy would only consume your valuable time. For example, you need access to metrics like NPS, average response time and others like it to make sure you come up with relevant strategies that help you retain more customers. 8: Average Revenue Per Account. #9:

Metrics 142

Metrics Customer retention SaaS Surveys 142

Education Services Group

APRIL 27, 2022

I’m not going to waste time trying to document how to correctly (mathematically) calculate all the three letter acronyms—but feel free to check out our Customer Success Definitions, Calculations, and Lingo…Oh My! Instead, I want to do some level setting on some specific metrics and flaws I see in the industry.

Metrics 98

Metrics Surveys SaaS CRM 98

AWS Machine Learning

MARCH 14, 2025

Although automated metrics are fast and cost-effective, they can only evaluate the correctness of an AI response, without capturing other evaluation dimensions or providing explanations of why an answer is problematic. Human evaluation, although thorough, is time-consuming and expensive at scale.

Metrics 92

Metrics Best practices Engineering APIs 92

AWS Machine Learning

OCTOBER 9, 2024

Amazon Lookout for Metrics is a fully managed service that uses machine learning (ML) to detect anomalies in virtually any time-series business or operational metrics—such as revenue performance, purchase transactions, and customer acquisition and retention rates—with no ML experience required. To learn more, see the documentation.

Metrics 87

Metrics APIs Engineering Accountability 87

AWS Machine Learning

NOVEMBER 15, 2024

For automatic model evaluation jobs, you can either use built-in datasets across three predefined metrics (accuracy, robustness, toxicity) or bring your own datasets. Regular evaluations allow you to adjust and steer the AI’s behavior based on feedback and performance metrics.

APIs 109

APIs Government Best practices Metrics 109

AWS Machine Learning

DECEMBER 6, 2023

Such data often lacks the specialized knowledge contained in internal documents available in modern businesses, which is typically needed to get accurate answers in domains such as pharmaceutical research, financial investigation, and customer support. For example, imagine that you are planning next year’s strategy of an investment company.

Analytics 124

Analytics APIs Engineering Construction 124

AWS Machine Learning

APRIL 19, 2023

The ability to effectively handle and process enormous amounts of documents has become essential for enterprises in the modern world. Due to the continuous influx of information that all enterprises deal with, manually classifying documents is no longer a viable option.

APIs 95

APIs Metrics Enterprise Best practices 95

AWS Machine Learning

NOVEMBER 7, 2024

SageMaker JumpStart is a machine learning (ML) hub that provides a wide range of publicly available and proprietary FMs from providers such as AI21 Labs, Cohere, Hugging Face, Meta, and Stability AI, which you can deploy to SageMaker endpoints in your own AWS account. This logic sits in a hybrid search component.

Enterprise 110

Enterprise APIs Government Accountability 110

Callminer

AUGUST 1, 2017

Metrics, Measure, and Monitor – Make sure your metrics and associated goals are clear and concise while aligning with efficiency and effectiveness. Make each metric public and ensure everyone knows why that metric is measured. Jeff Greenfield is the co-founder and chief operating officer of C3 Metrics.

Contact Center 334

Contact Center Call Center Average Handle Time Real estate 334

AWS Machine Learning

FEBRUARY 25, 2025

This post shows how to configure an Amazon Q Business custom connector and derive insights by creating a generative AI-powered conversation experience on AWS using Amazon Q Business while using access control lists (ACLs) to restrict access to documents based on user permissions. Who are the data stewards for my proprietary database sources?

Enterprise 89

Enterprise Engineering APIs Accountability 89

AWS Machine Learning

MARCH 11, 2025

One of the most critical applications for LLMs today is Retrieval Augmented Generation (RAG), which enables AI models to ground responses in enterprise knowledge bases such as PDFs, internal documents, and structured data. How do Amazon Nova Micro and Amazon Nova Lite perform against GPT-4o mini in these same metrics?

Benchmark 99

Benchmark APIs Enterprise Scripts 99

AWS Machine Learning

FEBRUARY 21, 2025

Besides the efficiency in system design, the compound AI system also enables you to optimize complex generative AI systems, using a comprehensive evaluation module based on multiple metrics, benchmarking data, and even judgements from other LLMs. The DSPy lifecycle is presented in the following diagram in seven steps.

Benchmark 82

Benchmark Metrics Engineering Feedback 82

CSM Magazine

JANUARY 20, 2025

Link your WhatsApp Business account to your organization’s professional phone number for added credibility. A WhatsApp Shared Inbox for Teams allows multiple support agents to respond to customer messages from the same WhatsApp account. Attach PDFs such as invoices, receipts, or warranty documentation directly in the chat.

Customer Service 52

Customer Service Metrics Accountability Analytics 52

AWS Machine Learning

JANUARY 29, 2025

Intelligent document processing , translation and summarization, flexible and insightful responses for customer support agents, personalized marketing content, and image and code generation are a few use cases using generative AI that organizations are rolling out in production.

Enterprise 84

Enterprise Government Accountability Finance 84

AWS Machine Learning

JUNE 20, 2024

In addition, RAG architecture can lead to potential issues like retrieval collapse , where the retrieval component learns to retrieve the same documents regardless of the input. This makes it difficult to apply standard evaluation metrics like BERTScore ( Zhang et al.

Metrics 132

Metrics Engineering Accountability Benchmark 132

BlueOcean

MARCH 24, 2025

Its a dynamic document that, like your partnership, requires time and attention. It also holds everyone accountable for the role theyre supposed to play. The contact center SOW will outline exactly what and how often metrics are to be reported and analyzed. Do metrics need to be adjusted?

Contact Center 62

Contact Center Automotive outsourcing Analytics 62

AWS Machine Learning

NOVEMBER 15, 2024

Recall@5 is a specific metric used in information retrieval evaluation, including in the BEIR benchmark. decode("utf-8")) response = response["embeddings"]["float"][0] elif is_txt(doc): # Doc is a text file, encode it as a document with open(doc, "r") as fIn: text = fIn.read() print("Encode img desc:", doc, " - Content:", text[0:100]+".")

Benchmark 104

Benchmark Enterprise Construction Engineering 104

AWS Machine Learning

NOVEMBER 21, 2022

Organizations across industries such as retail, banking, finance, healthcare, manufacturing, and lending often have to deal with vast amounts of unstructured text documents coming from various sources, such as news, blogs, product reviews, customer support channels, and social media. Extract and analyze data from documents.

Scripts 86

Scripts Metrics APIs Healthcare 86

AWS Machine Learning

NOVEMBER 19, 2024

Its agent for software development can solve complex tasks that go beyond code suggestions, such as building entire application features, refactoring code, or generating documentation. Learn how they created specialized agents for different tasks like account management, repos, pipeline management, and more to help their developers go faster.

APIs 92

APIs Enterprise Best practices Government 92

AWS Machine Learning

MARCH 3, 2025

Designed for both image and document comprehension, Pixtral demonstrates advanced capabilities in vision-related tasks, including chart and figure interpretation, document question answering, multimodal reasoning, and instruction followingseveral of which are illustrated with examples later in this post. Pixtral_data/a01-000u-04.png'

Benchmark 86

Benchmark APIs Enterprise Construction 86

Outsource Consultants

FEBRUARY 18, 2025

This fosters a sense of shared ownership and accountability. Regular Meetings: Conduct regular business reviews to track progress on action plans, discuss performance metrics, and address any roadblocks that may arise. Documented Procedures: Document all service level agreements (SLAs) and operating procedures clearly and concisely.

Feedback 67

Feedback Customer centricity Best practices Engineering 67

Callminer

JANUARY 18, 2021

They are an easy way to track metrics and discover trends within your agents. “The nature of a call center operator’s job is very sensitive, as there is account information available every time they assist a customer. Implement call centre etiquette tests regularly. This is short-sighted. ” – F. .”

Best practices 226

Best practices Call Center Contact Center Scripts 226

AWS Machine Learning

MARCH 25, 2025

Automated safety guards Integrated Amazon CloudWatch alarms monitor metrics on an inference component. AlarmName This CloudWatch alarm is configured to monitor metrics on an InferenceComponent. For more information, check out the SageMaker AI documentation or connect with your AWS account team.

APIs 94

APIs Engineering Accountability Metrics 94

CX Accelerator

FEBRUARY 6, 2019

While we were looking at your account we saw some searches for McDonald Heating and Cooling and added that as a negative keyword to prevent any wrong number calls coming through your ads." I've never focused on this as a metric so I have a couple of questions - 1. How do you metric-ize this? So far it is looking great!

Contact Center 206

Contact Center B2C B2B Metrics 206

AWS Machine Learning

NOVEMBER 3, 2022

In Part 1 of this series, we discussed intelligent document processing (IDP), and how IDP can accelerate claims processing use cases in the insurance industry. We discussed how we can use AWS AI services to accurately categorize claims documents along with supporting documents. Part 1: Classification and extraction of documents.

Analytics 90

Analytics APIs Healthcare Big data 90

The Northridge Group

NOVEMBER 4, 2021

They learn that great coaches are deliberate about recognizing even small associate accomplishments, but also hold associates accountable for their improvements. While improving overall metrics is the end goal, coaching to metrics seldom brings sustainable results. Accountability is essential for coaches as well as associates.

Best practices 145

Best practices Coaching contact center associations Contact Center 145

AWS Machine Learning

NOVEMBER 16, 2022

When designing production CI/CD pipelines, AWS recommends leveraging multiple accounts to isolate resources, contain security threats and simplify billing-and data science pipelines are no different. Some things to note in the preceding architecture: Accounts follow a principle of least privilege to follow security best practices.

Accountability 95

Accountability Best practices Scripts Engineering 95

AWS Machine Learning

AUGUST 7, 2024

To find an answer, RAG takes an approach that uses vector search across the documents. Rather than scanning every single document to find the answer, with the RAG approach, you turn the texts (knowledge base) into embeddings and store these embeddings in the database. Generate questions from the document using an Amazon Bedrock LLM.

APIs 131

APIs Chatbots Metrics Education 131

CCNG

APRIL 20, 2022

For example, a digitized agent coaching system enables team leaders to document their support interactions with agents and simultaneously capture key metrics about every touchpoint relevant to their routine. Analysts can correlate workflow intelligence with desired outcomes such as CSAT, NPS, FCR and other vital metrics.?

Customer Experience 195

Customer Experience CCNG Gamification Analytics 195

AWS Machine Learning

FEBRUARY 5, 2025

Data sources We use Spack documentation RST (ReStructured Text) files uploaded in an Amazon Simple Storage Service (Amazon S3) bucket. Whenever the assistant returns it as a source, it will be a link in the specific portion of the Spack documentation and not the top of a source page. For example, Spack images on Docker Hub.

Engineering 72

Engineering Feedback Analytics Education 72