AI Resource Center
Build a better data pipeline
Case Study
Training data to build multi-lingual Conversational AI
High-quality audio data sourced, created, curated, and transcribed to train conversational AI in 27 languages.
Case Study
Named Entity Recognition (NER) Annotation for Clinical NLP
Well-Annotated and Gold Standard clinical text data to train/develop clinical NLP to build next version of Healthcare API.
Case Study
Image Collection & Annotation to enhance Image Recognition
High-quality image data sourced and annotated to train image recognition models for new smartphone series.
One Pager
Data De-Id Anonymization Platform
Get critical data de-identified by credentialed domain experts
One Pager
Data Annotation Platform
Unlock critical information in unstructured data from financial, insurance, etc.
One Pager
Medical Annotation Platform
NER helps organizations to extract critical information in unstructured medical data
Webinar
Future of Voice Technology
Voice Technology has the power to revolutionize how we communicate. Read more View Recording
Automatic Number Plate Recognition (ANPR) – AN Overview
The evolution of technology has enabled the innovation of many useful equipment to ease the human effort. Automatic Number Plate Recognition, being one such technology,
These are the TOP 10 Frequently asked questions (FAQs) about Data Labeling
Every ML Engineer wants to develop a reliable and accurate AI model. Data scientists spend nearly 80% of their time labeling and augmenting data. That’s
How do Siri and Alexa Understand What You’re Saying?
Voice assistants might be these cool, predominantly female voices that respond to your requests to find the nearest restaurant or the shortest route to the
Top Use Cases of Natural Language Processing in Healthcare
The global natural language processing market is slated to increase from $1.8 billion in 2021 to $4.3 billion in 2026, growing at a CAGR of
Synthetic data and its role in the world of AI – Benefits, Use cases, Types & Challenges
The latest adage of data being the new oil is true, and just like your regular fuel, it is becoming hard to come by. Yet,
The Necessary Guide to Content Moderation – Importance, types, and challenges
The digital world is constantly evolving, and one catalyst that differentiates this platform from the others is user-generated content. Although companies worldwide have their websites
The Complete Guide to Conversational AI
The Complete Guide to Conversational AI The Ultimate Buyers Guide 2022 Intro Types Advantages Data Challenges Pros & Cons of Data Types Use Cases Industries
In-House or Outsourced Data Annotation – Which Gives Better AI Results?
In 2020, 1.7 MB of data was created every second by people. And in the same year, we produced close to 2.5 quintillion data bytes
How does the Human-in-the-Loop Approach Enhances ML Model Performance?
Machine learning models are not made perfect – they are perfected over time, with training and testing. An ML algorithm, to be able to produce
The role of AI in Medical Image Annotation
The phenomenal advancements in machine learning and artificial intelligence have revolutionized the healthcare industry. The global market for AI in healthcare in 2016 was about
What is Audio / Speech Annotation With Example
We have all asked Alexa (or other voice assistants) some open-ended questions. Alexa, is the nearest pizza place open? Alexa, which restaurant in my location
What is AI Image Recognition and How Does it Work?
Human beings have the innate ability to distinguish and precisely identify objects, people, animals, and places from photographs. However, computers don’t come with the capability
What is Optical Character Recognition (OCR): Overview and its applications
Optical Character Recognition might sound intense and foreign to most of us, but we have been using this advanced technology more often. We use this
What is DDS & the importance of Training Data to train DDS Models
Everyone knows about the dangers of driving under the influence or texting while driving. However, there isn’t much attention given to driving under drowsiness. In
What is ADAS? Importance of Training Data to train ADAS Models
Most accidents related to vehicles happen due to human error. Although you can’t prevent all vehicular accidents, you can avoid a significant portion of them.
High-quality training data fuels high-performing autonomous vehicles
In the last decade or less, every automaker you met was excited about the prospects of self-driving cars flooding the market. While a few major
6 Proven Methods to Customizing Speech Data Collection
There are several different types of clients – some have a clear idea of how their speech data should be structured, and some are more
Importance of Gold-standard training data to train Vehicle Damage Detection Model
Artificial Intelligence has spread its usefulness and sophistication to several fields, and one such novel application of this advanced technology is detecting vehicular damage. Claiming
5 Questions to Ask Before You Hire Healthcare Data Labeling Company
The global market for artificial intelligence in the healthcare sector is estimated to rise from $ 1.426 billion in 2017 to $ 28.04 in 2025.
How to Mitigate Common Data Challenges in Conversational AI
We have all interacted with Conversational AI applications such as Alexa, Siri, and Google Home. These applications have made our day-to-day lives so much easier
Speech Recognition Training Data – Types, data collection, and applications
If you use Siri, Alexa, Cortana, Amazon Echo, or others as a part of your daily lives, you would accept that Speech recognition has become
How to Identify and fix AI Training data errors
Like software development that works on a code, developing working artificial intelligence and machine learning models requires high-quality data. The models require accurately labeled and
How much is the optimum volume of training data you need for an AI project?
A working AI model is built on solid, reliable, and dynamic datasets. Without rich and detailed AI training data at hand, it is certainly not
A comprehensive guide to Annotating & Labeling Videos for Machine Learning
A comprehensive guide to Video Annotating & Labeling for Machine Learning Intro What is Video Annotation? Its Purpose Video vs. Image Annotation Various Techniques Types
The State of Conversational AI 2022
The State ofConversational AI 2022 What isConversational AI? A programmatic and intelligent way ofoffering a conversational experience tomimic conversations with real people, throughdigital and telecommunication
Named Entity Recognition (NER) – The Concept, Types, and Applications
Every time we hear a word or read a text, we have the natural ability to identify and categorize the word into people, place, location,
How Data Collection Plays a Crucial Role in Developing Facial Recognition Models
Humans are adept at recognizing faces, but we also interpret expressions and emotions quite naturally. Research says we can identify personally familiar faces within 380ms
Shaip Ensures High-Quality AI Training Data For your AI Models
The success of any AI model hinges on the quality of data fed into the system. ML systems run on large quantities of data, but
What is Data Collection? Everything a Beginner Needs to Know
Intelligent #AI/ #ML models are everywhere, be it, Predictive healthcare models, proactive diagnosis,
22+ Most Sought Open-Source Datasets for Computer Vision
An AI algorithm is only as good as the data you feed it. It is neither a bold nor an unconventional statement. AI could have
Training data to build multi-lingual Conversational AI
High-quality audio data sourced, created, curated, and transcribed to train conversational AI in 27 languages.
Utterance data collection to build multi-lingual digital assistant
Delivered 7M+ Utterances with over 22k hours of audio data to build Multi-lingual digital assistants in 13 languages.
Named Entity Recognition (NER) for Clinical NLP
Well-Annotated and Gold Standard clinical text data to train/develop clinical NLP to build next version of Healthcare API.
Image Collection & Annotation to enhance Image Recognition
High-quality image data sourced and annotated to train image recognition models for new smartphone series.
Future of Voice Technology – Challenges & Opportunities
Voice Technology has the power to revolutionize how we communicate. This webinar is aimed to educate the participant on ‘How voice tech can be utilized in any domain’ and how various Conversational AI use cases are used to enrich end-user experience.
Data transforming Healthcare
Artificial intelligence (AI) has the potential to transform how healthcare is delivered. This webinar is aimed to educate the participant on ‘How data can be utilized in the domain of healthcare’ using case studies & about the training data sets and data processing.
Buyer’s Guide
Buyer’s Guide: Data Annotation / Labeling
So, you want to start a new AI/ML initiative and are realizing that finding good data will be one of the more challenging aspects of your operation. The output of your AI/ML model is only as good as the data you use to train it – so the expertise you apply to data aggregation, annotation, and labeling is of critical importance.
Buyer’s Guide: High-quality AI Training Data
In the world of artificial intelligence and machine learning, data training is inevitable. This is the process that makes machine learning modules accurate, efficient, and fully functional. The guide explores in detail what AI training data is, types of training data, training data quality, data collection & licensing, and more.
Buyer’s Guide: Complete Guide to Conversational AI
The chatbot you conversed with runs on an advanced conversational AI system that is trained, tested, and built using tons of speech recognition datasets. It is the fundamental process behind the technology that makes machines intelligent and this is exactly what we are about to discuss and explore.
Buyer’s Guide: AI Data Collection
Machines don’t have a mind of their own. They are devoid of opinions, facts, and capabilities such as reasoning, cognition, and more. To turn them into powerful mediums, you need algorithms that are developed based on data. Data that is relevant, contextual, and recent. The process of collecting such data for machines is called AI data collection.
Buyer’s Guide: Video Annotation and Labeling
It is a fairly common saying we’ve all heard. that a picture could say a thousand words, just imagine what a video could be saying? A million things, perhaps. None of the ground-breaking applications we’ve been promised, such as driverless cars or intelligent retail check-outs, is possible without video annotation.
Buyer’s Guide: Image Annotation for CV
Computer vision is all about making sense of the visual world to train computer vision applications. Its success completely boils down to what we call image annotation – the fundamental process behind the technology that makes machines make intelligent decisions and this is exactly what we are about to discuss and explore.
eBook
The Key to Overcoming AI Development Obstacles
There is indeed an incredible amount of data being generated every day: 2.5 quintillion bytes, according to Social Media Today. But that doesn’t mean it’s all worthy of training your algorithm. Some data is incomplete, some is low-quality, and some is just plain inaccurate, so using any of this faulty information will result in the same traits out of your (expensive) AI data innovation.
Automatic Number Plate Recognition (ANPR) – AN Overview
The evolution of technology has enabled the innovation of many useful equipment to ease the human effort. Automatic Number Plate Recognition, being one such technology,
These are the TOP 10 Frequently asked questions (FAQs) about Data Labeling
Every ML Engineer wants to develop a reliable and accurate AI model. Data scientists spend nearly 80% of their time labeling and augmenting data. That’s
How do Siri and Alexa Understand What You’re Saying?
Voice assistants might be these cool, predominantly female voices that respond to your requests to find the nearest restaurant or the shortest route to the
Top Use Cases of Natural Language Processing in Healthcare
The global natural language processing market is slated to increase from $1.8 billion in 2021 to $4.3 billion in 2026, growing at a CAGR of
Synthetic data and its role in the world of AI – Benefits, Use cases, Types & Challenges
The latest adage of data being the new oil is true, and just like your regular fuel, it is becoming hard to come by. Yet,
The Necessary Guide to Content Moderation – Importance, types, and challenges
The digital world is constantly evolving, and one catalyst that differentiates this platform from the others is user-generated content. Although companies worldwide have their websites
The Complete Guide to Conversational AI
The Complete Guide to Conversational AI The Ultimate Buyers Guide 2022 Intro Types Advantages Data Challenges Pros & Cons of Data Types Use Cases Industries
In-House or Outsourced Data Annotation – Which Gives Better AI Results?
In 2020, 1.7 MB of data was created every second by people. And in the same year, we produced close to 2.5 quintillion data bytes
How does the Human-in-the-Loop Approach Enhances ML Model Performance?
Machine learning models are not made perfect – they are perfected over time, with training and testing. An ML algorithm, to be able to produce
The role of AI in Medical Image Annotation
The phenomenal advancements in machine learning and artificial intelligence have revolutionized the healthcare industry. The global market for AI in healthcare in 2016 was about
What is Audio / Speech Annotation With Example
We have all asked Alexa (or other voice assistants) some open-ended questions. Alexa, is the nearest pizza place open? Alexa, which restaurant in my location
What is AI Image Recognition and How Does it Work?
Human beings have the innate ability to distinguish and precisely identify objects, people, animals, and places from photographs. However, computers don’t come with the capability
What is Optical Character Recognition (OCR): Overview and its applications
Optical Character Recognition might sound intense and foreign to most of us, but we have been using this advanced technology more often. We use this
What is DDS & the importance of Training Data to train DDS Models
Everyone knows about the dangers of driving under the influence or texting while driving. However, there isn’t much attention given to driving under drowsiness. In
What is ADAS? Importance of Training Data to train ADAS Models
Most accidents related to vehicles happen due to human error. Although you can’t prevent all vehicular accidents, you can avoid a significant portion of them.
High-quality training data fuels high-performing autonomous vehicles
In the last decade or less, every automaker you met was excited about the prospects of self-driving cars flooding the market. While a few major
6 Proven Methods to Customizing Speech Data Collection
There are several different types of clients – some have a clear idea of how their speech data should be structured, and some are more
Importance of Gold-standard training data to train Vehicle Damage Detection Model
Artificial Intelligence has spread its usefulness and sophistication to several fields, and one such novel application of this advanced technology is detecting vehicular damage. Claiming
5 Questions to Ask Before You Hire Healthcare Data Labeling Company
The global market for artificial intelligence in the healthcare sector is estimated to rise from $ 1.426 billion in 2017 to $ 28.04 in 2025.
How to Mitigate Common Data Challenges in Conversational AI
We have all interacted with Conversational AI applications such as Alexa, Siri, and Google Home. These applications have made our day-to-day lives so much easier
Speech Recognition Training Data – Types, data collection, and applications
If you use Siri, Alexa, Cortana, Amazon Echo, or others as a part of your daily lives, you would accept that Speech recognition has become
How to Identify and fix AI Training data errors
Like software development that works on a code, developing working artificial intelligence and machine learning models requires high-quality data. The models require accurately labeled and
How much is the optimum volume of training data you need for an AI project?
A working AI model is built on solid, reliable, and dynamic datasets. Without rich and detailed AI training data at hand, it is certainly not
A comprehensive guide to Annotating & Labeling Videos for Machine Learning
A comprehensive guide to Video Annotating & Labeling for Machine Learning Intro What is Video Annotation? Its Purpose Video vs. Image Annotation Various Techniques Types
The State of Conversational AI 2022
The State ofConversational AI 2022 What isConversational AI? A programmatic and intelligent way ofoffering a conversational experience tomimic conversations with real people, throughdigital and telecommunication
Named Entity Recognition (NER) – The Concept, Types, and Applications
Every time we hear a word or read a text, we have the natural ability to identify and categorize the word into people, place, location,
How Data Collection Plays a Crucial Role in Developing Facial Recognition Models
Humans are adept at recognizing faces, but we also interpret expressions and emotions quite naturally. Research says we can identify personally familiar faces within 380ms
Shaip Ensures High-Quality AI Training Data For your AI Models
The success of any AI model hinges on the quality of data fed into the system. ML systems run on large quantities of data, but
What is Data Collection? Everything a Beginner Needs to Know
Intelligent #AI/ #ML models are everywhere, be it, Predictive healthcare models, proactive diagnosis,
22+ Most Sought Open-Source Datasets for Computer Vision
An AI algorithm is only as good as the data you feed it. It is neither a bold nor an unconventional statement. AI could have
The State of Conversational AI 2022
The State ofConversational AI 2022 What isConversational AI? A programmatic and intelligent way ofoffering a conversational experience tomimic conversations with real people, throughdigital and telecommunication
What is Data Collection? Everything a Beginner Needs to Know
Intelligent #AI/ #ML models are everywhere, be it, Predictive healthcare models, proactive diagnosis,
What is Data Labeling? Everything a Beginner Needs to Know
Download Infographics Intelligent AI models need to be trained extensively for being able to identify patterns, objects, and eventually make reliable decisions. However, the trained
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