AI Data

Research & Reports

Everest Group survey results: Enterprise readiness for generative AI adoption in customer experience management

Everest Group, supported by TELUS Digital, surveyed 200 customer experience leaders from around the world to determine their enterprise readiness for the adoption of generative AI (GenAI). Discover the results.

Generative AI

Everest Group survey results: Enterprise readiness for generative AI adoption in customer experience management

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AI Data

AI Best Practices

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Illustration showing lines separating into strands and becoming increasingly separated, meant to symbolize machine learning model drift

How to detect and mitigate machine learning model drift

Model drift degrades the accuracy of your ML model over time. Discover some best practices for detecting and mitigating it quickly and efficiently.

Illustration of an assembly line with bugs being removed from computer code via automated arms, meant to symbolize quality assurance in AI training data

Quality assurance best practices for AI training data

Hundreds of brightly colored lines on a black background. On the left of the image the colored lines are mixed together. In the middle of the image you can see the lines twisting and beginning to sort themselves into specific colors. On the right of the image, all lines are grouped together by color.

Automation: The antidote to overcoming data labeling inefficiencies

AI Trends

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What is the biggest hurdle for AI innovation?

In this article, we take a closer look at how a shortage of AI training data can affect tech innovation.

What is the biggest hurdle for AI innovation?

In this article, we take a closer look at how a shortage of AI training data can affect tech innovation.

AI Use Cases

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Podcast

What does customer loyalty look like in the age of AI?

On this episode, we ask big questions about how customer loyalty is formed — and how AI can be leveraged to build stronger connections with customers.

Two women sit in front of computer monitors doing annotation work.

Automotive

Creating annotation work opportunities through impact sourcing

Training a recommendation engine through image classification

Computer Vision

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Automotive

Does data hold the key to autonomous vehicle safety?

Experts believe autonomous vehicles will substantially improve road safety. Discover how large, diverse and accurate datasets are enabling this vision.

Two people with virtual reality (VR) goggles meant to symbolize the metaverse

The expanding frontiers of computer vision in the metaverse

Cars with bounding boxes to show image annotation

Automotive

Building high-quality 3D flash lidar datasets for autonomous vehicles

Data Annotation

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Research & Reports

Everest Group Data Annotation and Labeling (DAL) Solutions for AI/ML PEAK Matrix® Assessment 2024

Discover why TELUS Digital has been named a Leader in Everest Group's Data Annotation and Labeling (DAL) Solutions for AI/ML PEAK Matrix® Assessment 2024.

IDC MarketScape: Worldwide Data Labeling Software 2023 Vendor Assessment

Visualization of the interaction of self-driving autonomous vehicles.

Automotive

Enhancing an autonomous vehicle bot’s scenario understanding with tailored fine-tuning datasets

Data Collection

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Automotive

ADAS field operations testing: Four essential considerations for program success

Discover the processes involved in field operations testing for enhancing advanced driver assistance systems and key considerations for program success.

Illustration of connected dots, meant to represent governance in AI data collection.

Data governance with AI data collection

Five pitfalls to avoid before you start collecting data

Data Validation & Relevance

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Case Study

Technology

Facilitating transactional review and online shopping services for a global tech giant

Examine how TELUS Digital evaluated high-quality data and merchant ratings to enhance the customer experience.

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How do recommender systems facilitate great CX?

Travel & Hospitality

Improving search relevance for a fast-growing unicorn

Generative AI

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Illustration of various forms fine-tuning methods for large language models, including fine-tuning, prompt engineering, RLHF and RAG. Each of these methods is illustrated with iconography and shown to be connected

Fine-tuning large language models: A primer

Companies are eager to leverage the benefits generative AI (GenAI) offers. Implementing the technology, however, isn't a 'plug-and-play' process. Instead, it hinges on a critical task — fine-tuning a pretrained large language model (LLM) to be a specialist at your intended domain or application.

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Crafting production-grade GenAI applications

Two people and a robot at a table, with the robot shaking one person's hand, all meant to symbolize chatbot empathy

How empathy in your large language model can improve your CX

Linguistic Annotation

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Illustration of a person speaking into a microphone with a smiling robot listening, meant to symbolize natural language processing

Natural language processing: The power behind today's large language models

Large language models show incredible capabilities. Learn about the technology behind them and how they came to be the powerful machines they are today.

Are we headed for an AI data shortage?

Technology

Building a multilingual dataset with high-quality data collection and annotation

Responsible AI

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Brochure

Humanity-in-the-loop

If technology isn’t human-centered, who is it for?

We craft unique and enduring experiences for the brands we serve and their end customers while seeking positive outcomes for global citizens, our communities, team members and partners. In our work developing and deploying innovative technologies, we are guided by a set of ethical principles that we call humanity-in-the-loop.

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How to build responsible AI practices into your organization

Connected dots in a wave-like pattern meant to symbolize AI data

Promoting responsible AI with three innovative offerings

Check out our solutions

Enrich your data with our range of human-annotation services at scale.

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AI Data

AI Data

Everest Group survey results: Enterprise readiness for generative AI adoption in customer experience management

Everest Group survey results: Enterprise readiness for generative AI adoption in customer experience management

Building trust in generative AI

A practical guide to GenAI applications for customer experience management

Meeting the complex data annotation requirements of a unique non-profit organization

AI Data

AI Best Practices

How to detect and mitigate machine learning model drift

Quality assurance best practices for AI training data

Automation: The antidote to overcoming data labeling inefficiencies

AI Trends

What is the biggest hurdle for AI innovation?

What is the biggest hurdle for AI innovation?

AI Use Cases

What does customer loyalty look like in the age of AI?

Creating annotation work opportunities through impact sourcing

Training a recommendation engine through image classification

Computer Vision

Does data hold the key to autonomous vehicle safety?

The expanding frontiers of computer vision in the metaverse

Building high-quality 3D flash lidar datasets for autonomous vehicles

Data Annotation

Everest Group Data Annotation and Labeling (DAL) Solutions for AI/ML PEAK Matrix® Assessment 2024

IDC MarketScape: Worldwide Data Labeling Software 2023 Vendor Assessment

Enhancing an autonomous vehicle bot’s scenario understanding with tailored fine-tuning datasets

Data Collection

ADAS field operations testing: Four essential considerations for program success

Data governance with AI data collection

Five pitfalls to avoid before you start collecting data

Data Validation & Relevance

Facilitating transactional review and online shopping services for a global tech giant

How do recommender systems facilitate great CX?

Improving search relevance for a fast-growing unicorn

Generative AI

Fine-tuning large language models: A primer

Crafting production-grade GenAI applications

How empathy in your large language model can improve your CX

Linguistic Annotation

Natural language processing: The power behind today's large language models

Are we headed for an AI data shortage?

Building a multilingual dataset with high-quality data collection and annotation

Responsible AI

Humanity-in-the-loop

How to build responsible AI practices into your organization

Promoting responsible AI with three innovative offerings

Check out our solutions