APIs and Government - Customer Contact Central

Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning

NOVEMBER 14, 2024

Customers can use the SageMaker Studio UI or APIs to specify the SageMaker Model Registry model to be shared and grant access to specific AWS accounts or to everyone in the organization. This streamlines the ML workflows, enables better visibility and governance, and accelerates the adoption of ML models across the organization.

Government

Government Management APIs Accountability

Govern generative AI in the enterprise with Amazon SageMaker Canvas

AWS Machine Learning

SEPTEMBER 23, 2024

This is crucial for compliance, security, and governance. In this post, we analyze strategies for governing access to Amazon Bedrock and SageMaker JumpStart models from within SageMaker Canvas using AWS Identity and Access Management (IAM) policies. We provide code examples tailored to common enterprise governance scenarios.

Government

Government Enterprise APIs Accountability

Improve governance of models with Amazon SageMaker unified Model Cards and Model Registry

AWS Machine Learning

NOVEMBER 13, 2024

You can now register machine learning (ML) models in Amazon SageMaker Model Registry with Amazon SageMaker Model Cards , making it straightforward to manage governance information for specific model versions directly in SageMaker Model Registry in just a few clicks.

Government

Government Engineering Metrics APIs

Governing ML lifecycle at scale: Best practices to set up cost and usage visibility of ML workloads in multi-account environments

AWS Machine Learning

NOVEMBER 14, 2024

This post outlines steps you can take to implement a comprehensive tagging governance strategy across accounts, using AWS tools and services that provide visibility and control. Tagging is an effective scaling mechanism for implementing cloud management and governance strategies.

Government

Government Best practices Accountability APIs

Governing the ML lifecycle at scale: Centralized observability with Amazon SageMaker and Amazon CloudWatch

AWS Machine Learning

OCTOBER 29, 2024

This post is part of an ongoing series on governing the machine learning (ML) lifecycle at scale. To start from the beginning, refer to Governing the ML lifecycle at scale, Part 1: A framework for architecting ML workloads using Amazon SageMaker. Configure centralized logging to API calls across multiple accounts using CloudTrail.

Government

Government Metrics Accountability APIs

Use the ApplyGuardrail API with long-context inputs and streaming outputs in Amazon Bedrock

AWS Machine Learning

JULY 31, 2024

The new ApplyGuardrail API enables you to assess any text using your preconfigured guardrails in Amazon Bedrock, without invoking the FMs. In this post, we demonstrate how to use the ApplyGuardrail API with long-context inputs and streaming outputs. For example, you can now use the API with models hosted on Amazon SageMaker.

APIs

APIs Banking Best practices Engineering

How Deltek uses Amazon Bedrock for question and answering on government solicitation documents

AWS Machine Learning

AUGUST 9, 2024

This post provides an overview of a custom solution developed by the AWS Generative AI Innovation Center (GenAIIC) for Deltek , a globally recognized standard for project-based businesses in both government contracting and professional services. Deltek serves over 30,000 clients with industry-specific software and information solutions.

Government

Government Healthcare Construction Engineering

Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning

NOVEMBER 7, 2024

We also dive deeper into access patterns, governance, responsible AI, observability, and common solution designs like Retrieval Augmented Generation. It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. API Gateway is serverless and hence automatically scales with traffic.

Enterprise

Enterprise APIs Government Accountability

Use Amazon SageMaker Model Card sharing to improve model governance

AWS Machine Learning

AUGUST 31, 2023

The framework that gives systematic visibility into ML model development, validation, and usage is called ML governance. During AWS re:Invent 2022, AWS introduced new ML governance tools for Amazon SageMaker which simplifies access control and enhances transparency over your ML projects.

Government

Government Accountability Enterprise Best practices

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

AWS Machine Learning

OCTOBER 2, 2024

However, scaling up generative AI and making adoption easier for different lines of businesses (LOBs) comes with challenges around making sure data privacy and security, legal, compliance, and operational complexities are governed on an organizational level. In this post, we discuss how to address these challenges holistically.

Government

Government APIs Enterprise Best practices

Improve governance of your machine learning models with Amazon SageMaker

AWS Machine Learning

DECEMBER 1, 2022

Overview of model governance. Model governance is a framework that gives systematic visibility into model development, validation, and usage. Model governance is applicable across the end-to-end ML workflow, starting from identifying the ML use case to ongoing monitoring of a deployed model through alerts, reports, and dashboards.

Government

Government Metrics APIs Engineering

Secure Amazon SageMaker Studio presigned URLs Part 3: Multi-account private API access to Studio

AWS Machine Learning

APRIL 11, 2023

These customers need to balance governance, security, and compliance against the need for machine learning (ML) teams to quickly access their data science environments in a secure manner. We also introduce a logical construct of a shared services account that plays a key role in governance, administration, and orchestration.

APIs

APIs Accountability Scripts Enterprise

Build an internal SaaS service with cost and usage tracking for foundation models on Amazon Bedrock

AWS Machine Learning

FEBRUARY 9, 2024

IT teams are responsible for helping the LOB innovate with speed and agility while providing centralized governance and observability. A software as a service (SaaS) layer for foundation models can provide a simple and consistent interface for end-users, while maintaining centralized governance of access and consumption.

SaaS

SaaS APIs Government Accountability

Preparing Your Business for the API Economy

Nexmo

MAY 7, 2019

Partly, that’s code they write themselves but what makes modern software development so effective is that developers can easily build on the work of others through APIs. When you think of APIs it’s likely that some big names come to mind: Nexmo, the Vonage API platform; Stripe for payments; or one of the new Open Banking APIs.

APIs

APIs Airlines Banking Government

ChatGPT – is it the answer to customer service?

CCNG

MAY 17, 2023

To work in a customer service environment ChatGPT will always need a well-managed Knowledge Management system for it to retrieve its answers from that allows them to govern the information and have full control of the narrative. Set the foundation for success with a system that delivers answers to customers through any channel.

Customer Service

Customer Service CCNG Government Chatbots

Use Amazon SageMaker Model Cards sharing to improve model governance

AWS Machine Learning

AUGUST 31, 2023

The framework that gives systematic visibility into ML model development, validation, and usage is called ML governance. During AWS re:Invent 2022, AWS introduced new ML governance tools for Amazon SageMaker which simplifies access control and enhances transparency over your ML projects.

Government

Government Accountability Enterprise Best practices

Considerations for addressing the core dimensions of responsible AI for Amazon Bedrock applications

AWS Machine Learning

NOVEMBER 15, 2024

For now, we consider eight key dimensions of responsible AI: Fairness, explainability, privacy and security, safety, controllability, veracity and robustness, governance, and transparency. When using the RetrieveAndGenerate API, the output includes the generated response, the source attribution, and the retrieved text chunks.

APIs

APIs Government Best practices Metrics

Facebook’s Conversion API – what marketers need to know

Infinity

MARCH 3, 2022

So, in autumn 2021, when Facebook partnered up with Amazon and launched the Conversion API Gateway, it was a very exciting day for Facebook advertisers. When talking Facebook and data, you’re likely to come across two key models – the Conversion API Gateway and the Facebook Pixel, but what’s the difference?

APIs

APIs Marketing Advertising Government

How Druva used Amazon Bedrock to address foundation model complexity when building Dru, Druva’s backup AI copilot

AWS Machine Learning

NOVEMBER 1, 2024

Customers use Druva Data Resiliency Cloud to simplify data protection, streamline data governance, and gain data visibility and insights. Dru on the backend decodes log data, deciphers error codes, and invokes API calls to troubleshoot. This approach allowed us to break the problem down into multiple steps: Identify the API route.

APIs

APIs Scripts Engineering Government

Generate AWS Resilience Hub findings in natural language using Amazon Bedrock

AWS Machine Learning

NOVEMBER 18, 2024

Amazon Bedrock is a fully managed service to build generative AI applications with foundation models (FMs) from leading AI companies such as Anthropic, Mistral AI, Meta, Stability AI, Cohere, AI21 Labs, and Amazon through a single API. A second Lambda function invokes the Amazon Bedrock API. is a Sr.

APIs

APIs Government Engineering Accountability

Automate emails for task management using Amazon Bedrock Agents, Amazon Bedrock Knowledge Bases, and Amazon Bedrock Guardrails

AWS Machine Learning

NOVEMBER 19, 2024

Amazon Bedrock is a fully managed service that makes foundation models (FMs) from leading AI startups and Amazon Web Services available through an API, so you can choose from a wide range of FMs to find the model that is best suited for your use case.

APIs

APIs Management Engineering Enterprise

Create a Generative AI Gateway to allow secure and compliant consumption of foundation models

AWS Machine Learning

SEPTEMBER 28, 2023

Regulated and compliance-oriented industries, such as financial services, healthcare and life sciences, and government institutes, face unique challenges in ensuring the secure and responsible consumption of these models. In addition, API Registries enabled centralized governance, control, and discoverability of APIs.

APIs

APIs Government Enterprise Engineering

How Reveal’s Logikcull used Amazon Comprehend to detect and redact PII from legal documents at scale

AWS Machine Learning

NOVEMBER 1, 2023

In the legal system, discovery is the legal process governing the right to obtain and the obligation to produce non-privileged matter relevant to any party’s claims or defenses in litigation. This two pass solution was made possible by using the ContainsPiiEntities and DetectPiiEntities APIs.

APIs

APIs Government Engineering Telecommunications

A progress update on our commitment to safe, responsible generative AI

AWS Machine Learning

JULY 10, 2024

We’ve created more than 10 AI Service Cards thus far to deliver transparency for our customers as part of our comprehensive development process that addresses fairness, explainability, veracity and robustness, governance, transparency, privacy and security, safety, and controllability.

Government

Government Education Best practices Benchmark

Knowledge Bases for Amazon Bedrock now supports hybrid search

AWS Machine Learning

MARCH 1, 2024

Use hybrid search and semantic search options via SDK When you call the Retrieve API, Knowledge Bases for Amazon Bedrock selects the right search strategy for you to give you most relevant results. You have the option to override it to use either hybrid or semantic search in the API.

APIs

APIs Finance Chatbots Enterprise

Enhance customer service efficiency with AI-powered summarization using Amazon Transcribe Call Analytics

AWS Machine Learning

APRIL 30, 2024

Transcribe Call Analytics is a generative AI-powered API for generating highly accurate call transcripts and extracting conversation insights to improve customer experience, agent productivity, and supervisor productivity. Simply turn the feature on from the Amazon Transcribe console or using the start_call_analytics_job API.

Analytics

Analytics APIs Customer Service Entertainment

Accenture creates a regulatory document authoring solution using AWS generative AI services

AWS Machine Learning

FEBRUARY 6, 2024

Companies face complex regulations and extensive approval requirements from governing bodies like the US Food and Drug Administration (FDA). Users then review and edit the documents, where necessary, and submit the same to the central governing bodies. This post is co-written with Ilan Geller, Shuyu Yang and Richa Gupta from Accenture.

Government

Government APIs industry solution Education

Build an Amazon SageMaker Model Registry approval and promotion workflow with human intervention

AWS Machine Learning

JANUARY 10, 2024

The solution uses AWS Lambda , Amazon API Gateway , Amazon EventBridge , and SageMaker to automate the workflow with human approval intervention in the middle. The approver approves the model by following the link in the email to an API Gateway endpoint. API Gateway invokes a Lambda function to initiate model updates.

APIs

APIs Construction Engineering Analytics

How Veritone uses Amazon Bedrock, Amazon Rekognition, Amazon Transcribe, and information retrieval to update their video search pipeline

AWS Machine Learning

MAY 7, 2024

With a decade of enterprise AI experience, Veritone supports the public sector, working with US federal government agencies, state and local government, law enforcement agencies, and legal organizations to automate and simplify evidence management, redaction, person-of-interest tracking, and eDiscovery.

APIs

APIs Advertising Entertainment Metrics

Unleashing the power of generative AI: Verisk’s journey to an Instant Insight Engine for enhanced customer support

AWS Machine Learning

MAY 9, 2024

Data governance – With a wide variety of users accessing the platform and with different users having access to different data, data governance and isolation was paramount. First, they used the Amazon Kendra Retrieve API to get multiple relevant passages and excerpts based on keyword search.

Engineering

Engineering Customer Support APIs Government

How Aviva built a scalable, secure, and reliable MLOps platform using Amazon SageMaker

AWS Machine Learning

OCTOBER 3, 2024

The framework implements the infrastructure deployment from a primary governance account to separate development, staging, and production accounts. The governance components, which facilitate model promotions with consistent processes across accounts, have been integrated into the development account.

APIs

APIs Construction Engineering Accountability

Alida gains deeper understanding of customer feedback with Amazon Bedrock

AWS Machine Learning

MARCH 4, 2024

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

Feedback

Feedback APIs Engineering Surveys

Your guide to generative AI and ML at AWS re:Invent 2024

AWS Machine Learning

NOVEMBER 19, 2024

Plus, learn how to evolve from data aggregation to data semantics to support data-driven applications while maintaining flexibility and governance. Learn about Amazon SageMaker tooling for model governance, bias, explainability, and monitoring, and about transparency in the form of service cards as potential risk mitigation strategies.

APIs

APIs Enterprise Best practices Government

Securing MLflow in AWS: Fine-grained access control with AWS native services

AWS Machine Learning

MAY 8, 2023

It offers many native capabilities to help manage ML workflows aspects, such as experiment tracking, and model governance via the model registry. This can be a challenge for enterprises in regulated industries that need to keep strong model governance for audit purposes. Now let’s dive deeper into the details. Adds an IAM authorizer.

APIs

APIs Government Accountability Scripts

Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning

JANUARY 5, 2024

MLOps – Model monitoring and ongoing governance wasn’t tightly integrated and automated with the ML models. Reusability – Without reusable MLOps frameworks, each model must be developed and governed separately, which adds to the overall effort and delays model operationalization.

Management

Management APIs Engineering Government

Use Amazon SageMaker Studio with a custom file system in Amazon EFS

AWS Machine Learning

OCTOBER 17, 2024

Improved data governance and security – The shared EFS directory, being centrally managed by the AWS infrastructure admin, can provide improved data governance and security. You should have an AWS CloudTrail log file that logs the SageMaker API CreateUserProfile.

Government

Government Accountability APIs Engineering

Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

AWS Machine Learning

FEBRUARY 29, 2024

The Retrieve and RetrieveAndGenerate APIs allow your applications to directly query the index using a unified and standard syntax without having to learn separate APIs for each different vector database, reducing the need to write custom index queries against your vector store.

APIs

APIs Healthcare Scripts Enterprise

Design secure generative AI application workflows with Amazon Verified Permissions and Amazon Bedrock Agents

AWS Machine Learning

OCTOBER 14, 2024

Agents automatically call the necessary APIs to interact with the company systems and processes to fulfill the request. The App calls the Claims API Gateway API to run the claims proxy passing user requests and tokens. Claims API Gateway runs the Custom Authorizer to validate the access token.

APIs

APIs Construction Government Big data

Enhance conversational AI with advanced routing techniques with Amazon Bedrock

AWS Machine Learning

APRIL 24, 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 using a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI.

APIs

APIs Engineering Metrics Management

Access control for vector stores using metadata filtering with Knowledge Bases for Amazon Bedrock

AWS Machine Learning

JULY 2, 2024

With this access control capability, you can safely use retrieval across different user groups or scenarios while complying with company specific data governance policies and regulations. The following code snippet demonstrates how to call the retrieve_and_generate API using the Boto3 library in Python.

Healthcare

Healthcare APIs Government Accountability

Generative AI for agriculture: How Agmatix is improving agriculture with Amazon Bedrock

AWS Machine Learning

NOVEMBER 12, 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, Mistral AI, Stability 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.

Analytics

Analytics APIs Engineering Technology

Announcing enhanced table extractions with Amazon Textract

AWS Machine Learning

JUNE 7, 2023

Amazon Textract has a Tables feature within the AnalyzeDocument API that offers the ability to automatically extract tabular structures from any document. We walk through how to use these improvements through code examples to use the API and process the response with the Amazon Textract Textractor library.

APIs

APIs Real estate Government Marketing

Elevate RAG for numerical analysis using Amazon Bedrock Knowledge Bases

AWS Machine Learning

SEPTEMBER 25, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing FMs from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability 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.

APIs

APIs Call flow Accountability Technology

Enhance your media search experience using Amazon Q Business and Amazon Transcribe

AWS Machine Learning

JULY 30, 2024

The response from API calls are displayed to the end-user. Use metadata to assign values to index attributes for sorting, filtering, and faceting your search results, or to specify access control lists to govern access to the files. The Mediasearch indexer finds and transcribes audio and video files stored in an S3 bucket.

APIs

APIs Accountability Management Entertainment

Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

Govern generative AI in the enterprise with Amazon SageMaker Canvas

Trending Sources

Improve governance of models with Amazon SageMaker unified Model Cards and Model Registry

Governing ML lifecycle at scale: Best practices to set up cost and usage visibility of ML workloads in multi-account environments

Governing the ML lifecycle at scale: Centralized observability with Amazon SageMaker and Amazon CloudWatch

Use the ApplyGuardrail API with long-context inputs and streaming outputs in Amazon Bedrock

How Deltek uses Amazon Bedrock for question and answering on government solicitation documents

Build a multi-tenant generative AI environment for your enterprise on AWS

Use Amazon SageMaker Model Card sharing to improve model governance

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

Improve governance of your machine learning models with Amazon SageMaker

Secure Amazon SageMaker Studio presigned URLs Part 3: Multi-account private API access to Studio

Build an internal SaaS service with cost and usage tracking for foundation models on Amazon Bedrock

Preparing Your Business for the API Economy

ChatGPT – is it the answer to customer service?

Use Amazon SageMaker Model Cards sharing to improve model governance

Considerations for addressing the core dimensions of responsible AI for Amazon Bedrock applications

Facebook’s Conversion API – what marketers need to know

How Druva used Amazon Bedrock to address foundation model complexity when building Dru, Druva’s backup AI copilot

Generate AWS Resilience Hub findings in natural language using Amazon Bedrock

Automate emails for task management using Amazon Bedrock Agents, Amazon Bedrock Knowledge Bases, and Amazon Bedrock Guardrails

Create a Generative AI Gateway to allow secure and compliant consumption of foundation models

How Reveal’s Logikcull used Amazon Comprehend to detect and redact PII from legal documents at scale

A progress update on our commitment to safe, responsible generative AI

Knowledge Bases for Amazon Bedrock now supports hybrid search

Enhance customer service efficiency with AI-powered summarization using Amazon Transcribe Call Analytics

Accenture creates a regulatory document authoring solution using AWS generative AI services

Build an Amazon SageMaker Model Registry approval and promotion workflow with human intervention

How Veritone uses Amazon Bedrock, Amazon Rekognition, Amazon Transcribe, and information retrieval to update their video search pipeline

Unleashing the power of generative AI: Verisk’s journey to an Instant Insight Engine for enhanced customer support

How Aviva built a scalable, secure, and reliable MLOps platform using Amazon SageMaker

Alida gains deeper understanding of customer feedback with Amazon Bedrock

Your guide to generative AI and ML at AWS re:Invent 2024

Securing MLflow in AWS: Fine-grained access control with AWS native services

Modernizing data science lifecycle management with AWS and Wipro

Use Amazon SageMaker Studio with a custom file system in Amazon EFS

Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

Design secure generative AI application workflows with Amazon Verified Permissions and Amazon Bedrock Agents

Enhance conversational AI with advanced routing techniques with Amazon Bedrock

Access control for vector stores using metadata filtering with Knowledge Bases for Amazon Bedrock

Generative AI for agriculture: How Agmatix is improving agriculture with Amazon Bedrock

Announcing enhanced table extractions with Amazon Textract

Elevate RAG for numerical analysis using Amazon Bedrock Knowledge Bases

Enhance your media search experience using Amazon Q Business and Amazon Transcribe

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