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Data Annotation

End-to-End Text Annotation

High-Quality Training Data for Automated Text Classification and Natural Language Processing

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High-Quality Text Annotation and Classification Services

With Innodata’s full suite of text annotation and classification services, you can scale your AI models and ensure model flexibility with high-quality annotated text data. Leverage Innodata’s deep annotation expertise to streamline text annotation and classification using active learning, NLP, and human experts-in-the-loop.

Data-Centric Approach

Our data-centric approach helps jump-start your models with the highest quality of labeled text data for your AI/ML models.

Multiple Configurations

With world-class workbenches, our services can be configurable to address any requirements for labeling and annotation, including support for any text data input format in 40+ languages.

Highly Secure

Multiple security features within our operations result in the strictest control and compliance in labeling or classifying your text data.

Industry-Specific
Ready

With our global workforce of 4,000+ domain-specific subject matter experts, you can rely on Innodata to annotate, classify, and validate exceptional text data for any industry-specific use case in any major language with confidence.

Quality Assurance, Validation, & Control

Innodata can support various annotation processes such as single pass, double pass, double pass blind, or inter-annotator agreement processes — giving you the highest-quality annotated data to ensure your AI/ML model accuracy.

Scalable Output In Any Format

Our services can simultaneously process thousands of text files from multiple sources across different locations. Additionally, Innodata can support, load, or build custom taxonomies and deliver annotated text data in formats such as JSON, HTML, or XML.

Our Expertise at Work Across Diverse Applications

Whether you need document classification or NER annotation to automate document recognition or build your NLP models, our best-in-class text annotation solution delivers ground truth data for any situation in 40+ languages.

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Content Classification

Build binary classifiers and other classification models for automatically categorizing your content.

Intent Identification

Analyze the intent behind user-generated content to determine the proper response or course of action.

Content Detection

Automatically detect the types of content present in textual data to support content moderation, such as hate speech and other types of inappropriate content.

Semantic Identification

Build and train models to automatically extract concepts and entities, such as people, organizations, places, or topics from textual data.

Risk Assessment

Find and evaluate potential risks involved in an organization or undertaking. Identify and filter data based on types of risks.

Sentiment Analysis

Identify the sentiment behind your text to populate relevant metrics and other data analytics.

Relationship Mapping

Build relationships from your semantic data to support the development of knowledge maps.

Medical Data Research

Drug search, discovery, and complex annotation of medical literature, healthcare records, and medical data — including medical concepts and diseases.

Legal Data Analysis

Manage contract analysis and identify critical data from legislations, statutes, rules & regulations, circulars, and case law.

Business Intelligence

Identify meaningful and useful business data to enable more effective operational insights and decision-making. Support company data analysis, insight, and benchmarking.

Text Annotation Workbenches to Create your Training Datasets and Train Your AI Models

Text Annotation Customer Success Stories

Multilingual Content Moderation for Global Social Media Platform

A leading social media platform needed to improve modeling for search query relevance, ad review and placement, sentiment analysis and toxicity, and content moderation.

Multilingual Content Moderation for Global Social Media Platform

Goal:

A leading social media platform needed to improve modeling for search query relevance, ad review and placement, sentiment analysis and toxicity, and content moderation.

Innodata's Solution:

Deploy world-class content moderation, data annotation services, platforms, and SMEs to support the success of business units throughout the entire company (product, advertising, design, trust, data science, etc.).

  • Content Moderation: Toxicity, Misinformation ID, and Brand Protection
  • Search Query: Relevance Metrics, Trends,  and Quality Assurance
  • Advertising Revenue: Products Classification and Placement

Result:

Helping to perfect AI modeling to increase user engagement, maximize ad revenue, and build trust with their community through content moderation.

Delivering 100% accurate ground truth data to train and accelerate AI models focused on the platform’s most mission-critical data-driven initiatives across the globe.

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Risk Assessment Financial Annotation for Global Financial Firm

A global financial services firm required the annotation of technical financial documents to train its AI platform to conduct risk assessments for investment portfolios.

Global Financial Services Firm Builds AI Capability for Risk Assessment

Goal:

Global financial services firm required the annotation of technical financial documents to train its AI platform to conduct risk assessments for investment portfolios.

Innodata's Solution: 

Innodata's subject matter experts created a taxonomy focused on model-relevant risk categories and risk stages. To bolster speed and ensure high-quality annotations throughout the articles, Innodata employed a combination of humans-in-the-loop and ML-enhanced technology. The articles were first run through Innodata's proprietary text annotation platform, which completed an auto annotation. Then experts did a round of annotations to ensure accuracy and reviewed any low confidence annotations. Finally, our quality assurance specialist reviewed and resolved any discrepancies. The platform and annotators labeled the risks associated with events, named individuals, and named companies within each article. They then identified risks within each article and assigned a risk category and level based on the agreed-upon taxonomy.

Result:

The leading global financial services company's risk assessment platform received a large annotated dataset of the highest quality based on thousands of relevant articles. This pristine data, along with the risk taxonomy provided, helped train and improve the model performance.

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Multilingual Text Annotation for Leading Booking Engine Chatbot

A leading travel aggregator and booking engine required highly accurate annotated datasets for a booking assistant bot that operates in multiple languages.

Travel Aggregator Deploys AI Booking Assistant Chatbot

Goal:

Leading travel aggregator and booking engine required highly accurate datasets for a booking assistant bot that operates in multiple languages.

Innodata's Solution: 

To reach the seamless performance expected by the travel aggregator and its customers, the chatbot needed to be trained for many utterances per intent in English, Chinese, and French. To achieve this, the Innodata team annotated incoming chatbot messages for any mention of specific hotels, occurrences of locations (including cities, regions, districts, and addresses), and categorized the intent of the utterances based on their subjective interpretation of the message. This process of annotating utterances and assigning labels from a taxonomy allowed the chatbot to understand customer intent from incoming messaging and provide relevant and accurate responses. To ensure the accuracy and quality of the annotations, the Innodata team utilized a double-blind pass process, in which two different annotators provide annotations and an adjudicator provides a judgement on any discrepancies between the annotations. 

Result:

The travel aggregator received highly accurate annotated and labeled datasets which enabled the booking assistant AI chatbot to appropriately respond to customer messages and inquiries with relevant information in multiple languages improving the net promoter score. 

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Annotation for Life Science Data Provider’s Drug Search & Discovery

A leading abstract and indexing scientific research discovery solution required annotated data to enhance its platform for drug search/discovery and research funding.

Life Science Data Provider Acquires Right Annotated Data for Drug Search & Discovery

Goal:

A leading abstract and indexing scientific research discovery solution required annotated data to enhance its platform to enable predictive and prescriptive analytics for drug discovery and research funding.

Innodata's Solution: 

To begin the process of creating high-quality labeled scientific datasets, Innodata's annotation experts set up their platform to automate the process of entity extraction to pull out relevant keywords and references from the source documents. Innodata's experts then annotated millions of pages of scientific data, research, and articles. They created structured XML datasets that could be used to train the AI platform in predictive and prescriptive analytics.

Result:

With these datasets, the research discovery solution was able to provide more insight and give its users actionable intelligence. This intelligence is then used by the customer to research fund attribution, drive investments of new drug development, and avoid patent infringement.

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The Innodata Process

An End-to-End Approach

Prepare

Consult with a dedicated account manager. Generate test pilot to fine-tune annotation specifications to meet client’s ML needs. Align text annotation goals. Establish quality metrics, KPIs, & SLAs. A flexible & iterative approach.

Activate

A tailored team of in-house SMEs are selected based on project requirements and individual domain expertise. Annotators complete a customized training program after which they receive weekly audit reports, showing the results of auto-validation, random QC spot checks, and KPI performance evaluations. ​

Launch

Our text annotation services and platform offer various workbenches with unparalleled control of annotation workflows. Time-to-value enhancers augment and streamline work. Highly accurate annotated data. Infinite scale. ​

Deliver

Continuous delivery of ground-truth annotated text data to power your text classification and NLP models. Secure data transfers. Strengthen model weaknesses with iterative batches to facilitate active learning. ​

Our Team of Data Experts

Our team is comprised of data experts with years of developing strategies that enable companies to manage and distribute data using AI-based solutions. Book a time that works for you, and let us help develop a custom solution for your unique needs.

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Pricing Packages

Text Annotation Services

We offer cost effective packages while maintaining the highest quality.  All of our packages include:  
  • Dedicated Account Manager
  • Team of Subject Matter Experts
  • Project Management Dashboard
  • Custom Reports
  • Customized SLAs
  • KPI Metrics
  • API Connection
  • Streamlined NDA Process
  • Transparent Pricing
  • World-Class 24/7 Support
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Innodata (NASDAQ: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. That’s why we’re on a mission to help the world’s leading technology companies and enterprises drive Generative AI / AI innovation. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 35+ year legacy delivering the highest quality data and outstanding outcomes for our customers.

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Text Annotation

High-Quality Training Data to Scale AI/ML Model Development