APIs, Engineering and industry standards - Customer Contact Central

Insights in implementing production-ready solutions with generative AI

AWS Machine Learning

APRIL 30, 2025

Standard development best practices and effective cloud operating models, like AWS Well-Architected and the AWS Cloud Adoption Framework for Artificial Intelligence, Machine Learning, and Generative AI , are key to enabling teams to spend most of their time on tasks with high business value, rather than on recurrent, manual operations.

Government

Government Engineering Enterprise APIs

Evaluate large language models for your machine translation tasks on AWS

AWS Machine Learning

JANUARY 7, 2025

For customers operating in global industries, potentially translating to and from over 10 languages, this approach can prove to be operationally complex and costly. The solution proposed in this post relies on LLMs context learning capabilities and prompt engineering. You should see a noticeable increase in the quality score.

Engineering

Engineering Metrics industry standards Finance

How 20 Minutes empowers journalists and boosts audience engagement with generative AI on Amazon Bedrock

AWS Machine Learning

MAY 21, 2024

While these tasks can feel like a chore, they are critical to search engine optimization (SEO) and therefore the audience reach of the article. 20 Minutes journalists select stories relevant to our audience and rewrite, edit, and expand on them to fit the editorial standards and unique tone our readership is used to.

Advertising

Advertising APIs Engineering industry standards

Achieve operational excellence with well-architected generative AI solutions using Amazon Bedrock

AWS Machine Learning

OCTOBER 2, 2024

It’s a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like Anthropic, Cohere, Meta, Mistral AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

Government

Government APIs Enterprise Best practices

Using Agents for Amazon Bedrock to interactively generate infrastructure as code

AWS Machine Learning

JULY 11, 2024

Agents for Amazon Bedrock automates the prompt engineering and orchestration of user-requested tasks. This solution uses Retrieval Augmented Generation (RAG) to ensure the generated scripts adhere to organizational needs and industry standards. Provide the Amazon S3 URI that links to the API schema for each action group.

Scripts

Scripts APIs Engineering industry standards

Best practices to build generative AI applications on AWS

AWS Machine Learning

MARCH 14, 2024

We provide an overview of key generative AI approaches, including prompt engineering, Retrieval Augmented Generation (RAG), and model customization. Building large language models (LLMs) from scratch or customizing pre-trained models requires substantial compute resources, expert data scientists, and months of engineering work.

Best practices

Best practices Engineering Chatbots Enterprise

Harnessing the power of enterprise data with generative AI: Insights from Amazon Kendra, LangChain, and large language models

AWS Machine Learning

NOVEMBER 7, 2023

Foundation Models Pharma Ad Generator – A specialized application tailored for the pharmaceutical industry. Harnessing the generative capabilities of foundational models, this tool creates convincing and compliant pharmaceutical advertisements, ensuring content adheres to industry standards and regulations.

Enterprise

Enterprise APIs Engineering Accountability

Building scalable, secure, and reliable RAG applications using Knowledge Bases for Amazon Bedrock

AWS Machine Learning

APRIL 23, 2024

Here are some features which we will cover: AWS CloudFormation support Private network policies for Amazon OpenSearch Serverless Multiple S3 buckets as data sources Service Quotas support Hybrid search, metadata filters, custom prompts for the RetreiveAndGenerate API, and maximum number of retrievals.

APIs

APIs Enterprise Scripts Accountability

Generate customized, compliant application IaC scripts for AWS Landing Zone using Amazon Bedrock

AWS Machine Learning

APRIL 18, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon with a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

Scripts

Scripts Best practices Engineering Accountability

Philips accelerates development of AI-enabled healthcare solutions with an MLOps platform built on Amazon SageMaker

AWS Machine Learning

NOVEMBER 16, 2023

Amazon SageMaker provides purpose-built tools for machine learning operations (MLOps) to help automate and standardize processes across the ML lifecycle. This enables Philips ML engineers and developers to provide updates, bug fixes, and future enhancements without disrupting the entire system.

Healthcare

Healthcare Government Engineering APIs

Your guide to generative AI and ML at AWS re:Invent 2023

AWS Machine Learning

NOVEMBER 22, 2023

Hear best practices for using unstructured (video, image, PDF), semi-structured (Parquet), and table-formatted (Iceberg) data for training, fine-tuning, checkpointing, and prompt engineering. This session uses the Claude 2 LLM as an example of how prompt engineering helps to solve complex customer use cases. Reserve your seat now!

Engineering

Engineering Best practices APIs Government

Scaling Thomson Reuters’ language model research with Amazon SageMaker HyperPod

AWS Machine Learning

SEPTEMBER 12, 2024

Thomson Reuters experimented with pre-training open source FMs, such as MPT, Flan-T5, and Mistral, and compared against industry standard commercial models, such as OpenAI’s GPT-4. These checks can be run during the cluster creation, update, and node replacement phase and can be easily enabled or disabled through HyperPod APIs.

Enterprise

Enterprise Engineering Technology industry standards

Scale and simplify ML workload monitoring on Amazon EKS with AWS Neuron Monitor container

AWS Machine Learning

JUNE 25, 2024

Solution overview The Neuron Monitor container solution provides a comprehensive monitoring framework for ML workloads on Amazon EKS, using the power of Neuron Monitor in conjunction with industry-standard tools like Prometheus , Grafana , and Amazon CloudWatch. Ziwen Ning is a software development engineer at AWS.

Metrics

Metrics Best practices Analytics Accountability

Your Customers Are Talking, But Are You Listening?

Call Journey

OCTOBER 20, 2018

Until recently, the industry standard for reviewing calls coming through a contact center oscillated below 2%. This trend is further spurred by the API economy and a rise of marketplaces such as AppFoundry, offering specialized, highly sophisticated, yet light solutions. Temkin quote. The name of the game is integration.

Scripts

Scripts Customer emotions industry standards Contact Center

Evaluate large language models for quality and responsibility

AWS Machine Learning

NOVEMBER 30, 2023

FM evaluations provides actionable insights from industry-standard science, that could be extended to support customer-specific use cases. We surveyed existing open-source evaluation frameworks and designed FMEval evaluation API with extensibility in mind. What is FMEval?

Construction

Construction Metrics industry standards Benchmark

JustCall Vs 8×8: Who Can Seal Your Business’ Fate?

JustCall

APRIL 5, 2023

Further, businesses that find their preferred integration missing can contact the JustCall engineering team to request a new integration. Moreover, JustCall users in the Premium and Custom plans get API and webhook access, which allows them to build bespoke solutions. MMS Available at <cost> per MMS sent or received in the US.

Interactive Voice Response

Interactive Voice Response Contact Center APIs Analytics

Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning

JANUARY 26, 2024

The goal of this post is to empower AI and machine learning (ML) engineers, data scientists, solutions architects, security teams, and other stakeholders to have a common mental model and framework to apply security best practices, allowing AI/ML teams to move fast without trading off security for speed.

Best practices

Best practices Government Engineering Accountability

Gemma is now available in Amazon SageMaker JumpStart

AWS Machine Learning

MARCH 13, 2024

fine_tuned_predictor= estimator.deploy() You can choose to deploy the model fine-tuned on conversation data in SageMaker endpoint with HuggingFace messages API feature as an alternative approach. Compare the model’s performance to benchmarks and industry standards. Analyze errors and biases to identify areas for improvement. **7.

Benchmark

Benchmark Scripts APIs Feedback

What is Call Center Compliance?

NobelBiz

APRIL 9, 2024

Standards Call Centers Must Follow In addition to specific regulations, call centers should adhere to industry standards and best practices, here are 10 of the most important standards any call center should follow: 1. How NobelBiz Omni+ can take your Contact Center to the Next Level? appeared first on NobelBiz.

Call Center

Call Center Telemarketing Healthcare Government

Operationalize LLM Evaluation at Scale using Amazon SageMaker Clarify and MLOps services

AWS Machine Learning

NOVEMBER 29, 2023

For example, the EU AI Act is tasked providing information on which datasets are used for training, what compute power is required to run the model, report model results against public/industry-standard benchmarks and share results of internal and external testing. Model fine-tuners want to solve specific tasks (e.g.

Benchmark

Benchmark Metrics Engineering APIs

Innovating at speed: BMW’s generative AI solution for cloud incident analysis

AWS Machine Learning

MARCH 5, 2025

The fully automated RCA agent correctly identifies the right root cause for most cases (measured at 85%), and helps engineers in terms of system understanding and real-time insights in their cases. Was there an inadvertent breaking change in recent API changes? Is the iOS app responsible for the outage, or the backend-for-frontend?

APIs

APIs Engineering Automotive Metrics

Minimize generative AI hallucinations with Amazon Bedrock Automated Reasoning checks

AWS Machine Learning

APRIL 1, 2025

Natural language to logic translation The system uses two complementary approaches: LLMs handle natural language understanding, and a symbolic reasoning engine performs mathematical validation. It can be accessed through both the Amazon Bedrock console and APIs, making it flexible for various implementation needs.

APIs

APIs Best practices Feedback Engineering

NeMo Retriever Llama 3.2 text embedding and reranking NVIDIA NIM microservices now available in Amazon SageMaker JumpStart

AWS Machine Learning

MARCH 18, 2025

NIM microservices provide straightforward integration into generative AI applications using industry-standard APIs and can be deployed with just a few lines of code, or with a few clicks on the SageMaker JumpStart console. In the following section, we use a sample text to do an inference request.

APIs

APIs Enterprise Engineering Accountability

Solve forecasting challenges for the retail and CPG industry using Amazon SageMaker Canvas

AWS Machine Learning

JANUARY 21, 2025

For example, business analysts who have no coding or cloud engineering expertise can quickly use Amazon SageMaker Canvas to upload their time-series data and make forecasting predictions. Retail and CPG organizations rely on industry standard methods in their approach to forecasting. One of these methods is quantiles.

Metrics

Metrics Enterprise Sales APIs

Customer Contact Central

Insights in implementing production-ready solutions with generative AI

Evaluate large language models for your machine translation tasks on AWS

Trending Sources

How 20 Minutes empowers journalists and boosts audience engagement with generative AI on Amazon Bedrock

Achieve operational excellence with well-architected generative AI solutions using Amazon Bedrock

Using Agents for Amazon Bedrock to interactively generate infrastructure as code

Best practices to build generative AI applications on AWS

Harnessing the power of enterprise data with generative AI: Insights from Amazon Kendra, LangChain, and large language models

Building scalable, secure, and reliable RAG applications using Knowledge Bases for Amazon Bedrock

Generate customized, compliant application IaC scripts for AWS Landing Zone using Amazon Bedrock

Philips accelerates development of AI-enabled healthcare solutions with an MLOps platform built on Amazon SageMaker

Your guide to generative AI and ML at AWS re:Invent 2023

Scaling Thomson Reuters’ language model research with Amazon SageMaker HyperPod

Scale and simplify ML workload monitoring on Amazon EKS with AWS Neuron Monitor container

Your Customers Are Talking, But Are You Listening?

Evaluate large language models for quality and responsibility

JustCall Vs 8×8: Who Can Seal Your Business’ Fate?

Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

Gemma is now available in Amazon SageMaker JumpStart

What is Call Center Compliance?

Operationalize LLM Evaluation at Scale using Amazon SageMaker Clarify and MLOps services

Innovating at speed: BMW’s generative AI solution for cloud incident analysis

Minimize generative AI hallucinations with Amazon Bedrock Automated Reasoning checks

NeMo Retriever Llama 3.2 text embedding and reranking NVIDIA NIM microservices now available in Amazon SageMaker JumpStart

Solve forecasting challenges for the retail and CPG industry using Amazon SageMaker Canvas

Stay Connected