APIs, Big data, Metrics and Technology - Customer Contact Central

How Amp on Amazon used data to increase customer engagement, Part 2: Building a personalized show recommendation platform using Amazon SageMaker

AWS Machine Learning

SEPTEMBER 9, 2022

This is Part 2 of a series on using data analytics and ML for Amp and creating a personalized show recommendation list platform. The platform has shown a 3% boost to customer engagement metrics tracked (liking a show, following a creator, enabling upcoming show notifications) since its launch in May 2022.

Personalization

Personalization APIs Engineering Metrics

Identify objections in customer conversations using Amazon Comprehend to enhance customer experience without ML expertise

AWS Machine Learning

APRIL 24, 2023

Since conversational AI has improved in recent years, many businesses have adopted cutting-edge technologies like AI-powered chatbots and AI-powered agent support to improve customer service while increasing productivity and lowering costs. API Gateway bypasses the request to Lambda. Lambda checks the format and stores it in DynamoDB.

APIs

APIs Customer Experience Feedback Chatbots

How Amp on Amazon used data to increase customer engagement, Part 1: Building a data analytics platform

AWS Machine Learning

SEPTEMBER 9, 2022

Amp wanted a scalable data and analytics platform to enable easy access to data and perform machine leaning (ML) experiments for live audio transcription, content moderation, feature engineering, and a personal show recommendation service, and to inspect or measure business KPIs and metrics. Solution overview.

Analytics

Analytics Engineering APIs Metrics

Webinars

How to Optimize Call Monitoring: Automate QA and Elevate Customer Experience

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Identify rooftop solar panels from satellite imagery using Amazon Rekognition Custom Labels

AWS Machine Learning

JULY 19, 2022

With rapid development in computer vision technology, several third-party tools use computer vision to analyze satellite images and identify objects (like solar panels) automatically. To test the model output, we use a Jupyter notebook to run Python code to detect custom labels in a supplied image by calling Amazon Rekognition APIs.

APIs

APIs Metrics Enterprise Government

Speed ML development using SageMaker Feature Store and Apache Iceberg offline store compaction

AWS Machine Learning

DECEMBER 21, 2022

SageMaker Feature Store automatically builds an AWS Glue Data Catalog during feature group creation. Customers can also access offline store data using a Spark runtime and perform big data processing for ML feature analysis and feature engineering use cases. Table formats provide a way to abstract data files as a table.

Scripts

Scripts Engineering APIs Big data

How Patsnap used GPT-2 inference on Amazon SageMaker with low latency and cost

AWS Machine Learning

JULY 24, 2023

They use big data (such as a history of past search queries) to provide many powerful yet easy-to-use patent tools. These tools have enabled Patsnap’s global customers to have a better understanding of patents, track recent technological advances, identify innovation trends, and analyze competitors in real time. client('sts').get_caller_identity()['Account']

APIs

APIs Engineering Construction Benchmark

Improve governance of your machine learning models with Amazon SageMaker

AWS Machine Learning

DECEMBER 1, 2022

With the SageMaker Python SDK, you can seamlessly update the Model card with evaluation metrics. Model cards provide model risk managers, data scientists, and ML engineers the ability to perform the following tasks: Document model requirements such as risk rating, intended usage, limitations, and expected performance.

Government

Government Metrics APIs Engineering

How SaaS Software Can Help Sync Your Sales & Support Teams

aircall

APRIL 16, 2021

Establish performance metrics (response time, retention, engagement, etc.). SaaS works well for a variety of general use cases, including: Data backup. Big data analytics. Flexibility – SaaS uses an open API (application programming interface) technology. 8) Failing to track metrics.

SaaS

SaaS Sales Coaching APIs

Developing advanced machine learning systems at Trumid with the Deep Graph Library for Knowledge Embedding

AWS Machine Learning

JULY 25, 2022

Trumid is a financial technology company building tomorrow’s credit trading network—a marketplace for efficient trading, information dissemination, and execution between corporate bond market participants. The bond trading market has traditionally involved offline buyer/seller matching processes aided by rules-based technology.

Scripts

Scripts Engineering Analytics APIs

BI with an IQ - Revisited

Xaqt

FEBRUARY 6, 2020

At the time, Latigent was the leading Business Intelligence provider for call centers, and we were focused on leveraging emerging technology to move that value proposition forward. technologies were first emerging. Back then, Artificial Intelligence, APIs, Robotic Process Automation (RPA), and even "Big Data" weren't things yet.

Contact Center

Contact Center Enterprise Call Center APIs

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

AWS Machine Learning

JANUARY 26, 2024

As your organization advances its use of emerging technologies such as generative AI and LLMs, overall organizational resiliency should be considered as a cornerstone of a layered defensive strategy to protect assets and lines of business from unintended consequences.

Best practices

Best practices Government Engineering Accountability

MLOps foundation roadmap for enterprises with Amazon SageMaker

AWS Machine Learning

JUNE 24, 2022

Building an MLOps foundation that can cover the operations, people, and technology needs of enterprise customers is challenging. Initial phase: During this phase, the data scientists are able to experiment and build, train, and deploy models on AWS using SageMaker services. Data lake and MLOps integration. MLOps maturity model.

Enterprise

Enterprise Engineering Accountability APIs

Build repeatable, secure, and extensible end-to-end machine learning workflows using Kubeflow on AWS

AWS Machine Learning

SEPTEMBER 9, 2022

Prior to our adoption of Kubeflow on AWS, our data scientists used a standardized set of tools and a process that allowed flexibility in the technology and workflow used to train a given model. This means that user access can be controlled on the Kubeflow UI but not over the Kubernetes API via Kubectl. Logging and monitoring.

Engineering

Engineering Healthcare APIs Scripts

Demystifying machine learning at the edge through real use cases

AWS Machine Learning

JUNE 15, 2022

Edge is a term that refers to a location, far from the cloud or a big data center, where you have a computer device (edge device) capable of running (edge) applications. IoT relates to physical objects embedded with technologies like sensors, processing ability, and software. But how does IoT correlate to ML@Edge?

Transportation

Transportation APIs Big data Wireless

Call Center Reporting - A New Paradigm

Xaqt

JUNE 22, 2020

The innovation quagmire in the Call Center Reporting and Analytics space is rooted in three key issues: Vendor's who's contact center suites are an amalgamation of various acquisitions, such as: Cisco, Avaya, Genesys, NICE and Verint have done a poor job of providing integrated data and reporting across their own portfolios.

Call Center

Call Center Contact Center Analytics Engineering

Why Access to Customer Data is Essential for Sales Performance

aircall

MARCH 19, 2021

With all the available customer data companies have at their disposal to enhance the performance of customer service, sales, and marketing efforts, a remarkable 73% of companies still do not use it effectively. And out of those who do practise data collection, only 12% analyze it. Best Practices of Customer Data Management.

Sales

Sales CRM Marketing Best practices

Model management for LoRA fine-tuned models using Llama2 and Amazon SageMaker

AWS Machine Learning

NOVEMBER 14, 2023

In the era of big data and AI, companies are continually seeking ways to use these technologies to gain a competitive edge. At the core of these cutting-edge solutions lies a foundation model (FM), a highly advanced machine learning model that is pre-trained on vast amounts of data.

Management

Management APIs Best practices Calibration

CREATING CREDIT UNION MEMBERS FOR LIFE

Enghouse Interactive

JULY 10, 2018

You may be wondering “How can credit unions keep this philosophy alive and thriving amidst a technology filled world?” With the rise of rise digital technologies members are looking to self-service first. For Partner Colorado, Enghouse’s use of open APIs allows integration with the in-house CRM.

Self service

Self service CRM Contact Center Analytics

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

AWS Machine Learning

MAY 8, 2023

In this post, we address these limitations by implementing the access control outside of the MLflow server and offloading authentication and authorization tasks to Amazon API Gateway , where we implement fine-grained access control mechanisms at the resource level using Identity and Access Management (IAM). Adds an IAM authorizer.

APIs

APIs Government Accountability Scripts

Designing generative AI workloads for resilience

AWS Machine Learning

FEBRUARY 1, 2024

Observability Besides the resource metrics you typically collect, like CPU and RAM utilization, you need to closely monitor GPU utilization if you host a model on Amazon SageMaker or Amazon Elastic Compute Cloud (Amazon EC2). He entered the big data space in 2013 and continues to explore that area.

Best practices

Best practices Engineering SaaS APIs

Generating value from enterprise data: Best practices for Text2SQL and generative AI

AWS Machine Learning

JANUARY 4, 2024

NLP SQL enables business users to analyze data and get answers by typing or speaking questions in natural language, such as the following: “Show total sales for each product last month” “Which products generated more revenue?” In entered the Big Data space in 2013 and continues to explore that area. Arghya Banerjee is a Sr.

Best practices

Best practices Enterprise Engineering APIs

Accelerating time-to-insight with MongoDB time series collections and Amazon SageMaker Canvas

AWS Machine Learning

DECEMBER 18, 2023

The SageMaker Canvas UI lets you seamlessly integrate data sources from the cloud or on-premises, merge datasets effortlessly, train precise models, and make predictions with emerging data—all without coding. Solution overview Users persist their transactional time series data in MongoDB Atlas.

Finance

Finance APIs Analytics Scripts

MLOps for batch inference with model monitoring and retraining using Amazon SageMaker, HashiCorp Terraform, and GitLab CI/CD

AWS Machine Learning

AUGUST 29, 2023

When a new version of the model is registered in the model registry, it triggers a notification to the responsible data scientist via Amazon SNS. If the model quality metric (for example, RMSE for regression and F1 score for classification) doesn’t meet a pre-specified criterion, the model quality check step is marked as failed.

Scripts

Scripts APIs Enterprise Accountability

Why Behavioural Data and Behavioural Analytics Have Become the Secret Ingredient for Product Led Growth!

SmartKarrot

JUNE 23, 2020

Without analytics, collation of behavioural data is a waste. Without analytics, CS teams can only rely on insufficient demographic data, or what’s called ‘vanity metrics. So, as Streaming, Sharing, Stealing: Big Data and the Future of Entertainment co-author Michael D. Remember: Data never lies .

Analytics

Analytics SaaS Upselling Entertainment

Customer Contact Central

How Amp on Amazon used data to increase customer engagement, Part 2: Building a personalized show recommendation platform using Amazon SageMaker