TrainAI Data Services Overview

TrainAI – AI data you can depend on from RWS, your responsible AI partner

High-quality, AI training data custom-tailored to your machine learning (ML) needs

The AI data challenge

Training AI requires data. LOTS of data. But not just any data will do – you need responsible AI data that’s targeted, accurate, and reliable to ensure ML model success.
Preparing AI training data is a monumental task that can take up the vast majority of your AI project time, leaving your team with precious little time to focus on developing, deploying, and evaluating your ML models and AI applications. RWS can help.
With a seamless blend of technological understanding and human intelligence, TrainAI by RWS provides complete, end-to-end data collection and content generation, data annotation or labelling, human-in-the-loop data validation, and generative AI data services for all types of AI data, in any language, at any scale, based on the principles of responsible AI. 
TrainAI provides reliable, targeted data for generative AI like large language models (LLMs), augmented intelligence, deep learning models, and more.
Train AI Data Services - RWS

Generative AI training and fine-tuning

Train and fine-tune your generative AI model with our comprehensive data or content creation, prompt engineering, reinforcement learning from human feedback (RLFH), and red teaming services, along with our proven domain expertise and locale-specific support.

Other types of AI we support

In addition to generative AI, TrainAI provides high-quality AI data to support the training and fine-tuning of a broad range of AI applications including: 
  • Descriptive AI models which describe and report data and information
  • Diagnostic AI applications which analyse data to identify the root causes of issues
  • Predictive AI systems which use historical data and statistical algorithms to predict future outcomes
  • Prescriptive AI engines which provide recommendations on actions to optimize results
  • And many more

AI data consulting

Whether you need to evaluate your current AI data strategy, detect and remove bias, address ML model exploitability, or test your AI, our team of experts will work with you to resolve even your most complex AI training data challenges.
Data Services for AI - Consulting - RWS

Why choose TrainAI?

TrainAI delivers:

AI applications powered by TrainAI data

Generative AI Large language models Search Virtual assistants Chatbots Facial recognition systems Optical character recognition Social media

Generative AI

Generative AI is a field of artificial intelligence that focuses on developing models capable of generating new text, audio, image, or video content that resembles human-created content. They use techniques such as deep learning and neural networks to understand patterns and generate unique, human-like outputs.
TrainAI provides a broad range of AI data services to train and fine-tune generative AI models including:
  • Prompt engineering: creating and refining prompt-response pairs to optimize model output
  • Model fine-tuning: reinforcement learning from human feedback (RLHF) including response rating, evaluation and editing, fact extraction and verification, and content moderation to improve model accuracy and reliability
  • Risk mitigation: red teaming or jailbreaking to uncover vulnerabilities such as inaccurate, hallucinatory, or potentially harmful responses from the model
  • Domain expertise: to produce domain-specific content or data across a broad range of industries to fine-tune the model
  • Locale support: creation, editing, and evaluation of locale-specific content or data to expand the model’s global reach

Large language models

Large language models (LLMs) are generative AI models that are trained on vast amounts of textual data to understand and generate human-like language. They consist of millions or even billions of parameters, enabling them to learn complex patterns and relationships in language.
AI training data plays a crucial role in improving today’s LLMs. TrainAI helps optimize the performance of LLMs by providing the quality AI training data they need to:
  • Learn grammar, vocabulary, and contextual understanding
  • Generate coherent and contextually relevant responses that reflect diversity of people, perspectives, and experiences
  • Grasp the intricacies of specific domains and cultures, including idiomatic expressions, nuanced cultural references, and domain-specific knowledge
  • Stay up to date with current trends and evolving language patterns


Search engines are the primary gateway for users to access information on the internet. Continuous improvement of search engine results is crucial for both users and advertisers. For users, better search results mean easier access to more accurate, relevant, and high-quality information. For advertisers, improved search results mean better ad campaign performance and ROI.
TrainAI’s search evaluators help improve search performance by:
  • Assessing the accuracy and relevance of search results based on specific queries or user intent, considering factors such as query interpretation, semantic understanding, and contextual relevance
  • Identifying instances of spam, irrelevant, low-quality content, and content that violates guidelines or misleads users
  • Evaluating the performance of search engine features and functionalities such as autocomplete, query suggestions, related searches, and knowledge panels

Virtual assistants

Virtual assistants are voice-enabled AI applications designed to perform various tasks and provide services to users through natural language interactions. They are trained on vast amounts of diverse and labelled AI training data which enables them to learn language patterns, grammar, semantic relationships, and contextual understanding. 
TrainAI provides a broad range of AI data services to help train virtual assistants including:
  • High-quality, locale-specific text and speech data annotated or labelled with correct intent, sentiment analysis, and more
  • Entity recognition including identifying and extracting specific entities such as names, dates, locations, and other relevant information from text or speech data
  • Dialog and conversational AI data which provides training examples of coherent and meaningful conversations, conversational nuances, and appropriate responses
  • Domain-specific AI data and expertise across a broad range of industries such as technology, life sciences, and finance, to train virtual assistants for specific contexts and specialized queries


Chatbots are designed to simulate human conversation through text or speech interactions. They use AI and natural language processing (NLP) techniques to understand user queries, interpret intent, and provide automated responses.
TrainAI offers the following AI data services to help train chatbots:
  • Intent classification and variation to enable chatbots to recognize and classify intents accurately, and understand user goals
  • Entity recognition to help chatbots extract specific entity information, such as names, dates, locations, or product details from user queries
  • Utterance generation dialog data to train chatbots to produce natural, coherent, and contextually appropriate replies to user inputs
  • Dialog flow and contextual understanding to help chatbots maintain coherent conversations, remember user context, and generate appropriate responses
  • User feedback and reinforcement learning to improve chatbot performance over time

Facial recognition systems

Facial recognition systems use AI algorithms to identify and verify individuals based on their facial features. They analyze facial patterns, such as the arrangement of eyes, nose, and mouth to create unique facial representations.
TrainAI provides the AI data required to train facial recognition models including:
  • Diverse face images representing different ethnicities, ages, genders, and other demographic criteria to mitigate bias and ensure reliable recognition across various populations
  • Labelled face images where each face is annotated with facial keypoint data to identify, for example, the position of eyes, nose, and mouth
  • Occlusion and pose variation data that includes various poses (different head angles) and occlusions (partially covered faces)
  • Adversarial and anti-spoofing data including manipulated images (adversarial), and samples of different spoofing techniques, such as printed photos or masks (anti-spoofing), designed to fool the model

Optical character recognition

Optical character recognition (OCR) is a technology that enables the automatic extraction and interpretation of text from images or scanned documents. It uses AI algorithms to recognize and convert printed or handwritten text into editable and searchable digital content.
TrainAI helps train OCR engines by providing:
  • Labelled character or word images where each character is annotated with its corresponding textual representation
  • Typographical variations of font and style to help the OCR engine recognize and interpret text accurately 
  • Locale-specific AI data to enable the model to correctly recognize and process text in different languages for different locales
  • Information about layout, structure, and logical components, such as paragraphs, headings, tables, or lists, to help the model understand a document’s hierarchical structure and extract text accordingly
  • Handwritten text samples to enable the OCR engine to recognize and convert handwritten text accurately

Social media

Social media platforms aim to enhance user experience and engagement by curating and personalizing the content displayed to its users. Every day, a monumental volume of content is uploaded onto social media networks, and that data must be screened, prioritized, and promoted to optimize user experience and engagement.
TrainAI supports social media networks in this effort by providing:
  • Locale-specific AI training data to expand the language coverage of social media platforms
  • Content moderation services including monitoring, reviewing, and controlling social media content to ensure compliance with community guidelines, platform policies, and legal requirements
  • Image and video classification to identify explicit or graphic content to help differentiate between safe and inappropriate imagery

Types of AI data delivered by TrainAI

Text data
Audio / speech data
Image data
Video data
Locale-specific data
Synthetic data

Our TrainAI community

Instead of crowdsourcing your data needs to anyone and hoping for the best, we deliver AI training data collected, annotated, and validated by our TrainAI community of active, vetted, skilled, and qualified AI data specialists based on your specific ML project requirements.
community members
language variants

Industries we serve

RWS has dedicated teams with deep expertise in almost every industry sector, so you can rest assured that your global AI training data will be accurate, effective, and compliant.
Technology-agnostic approach

Let's connect

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