bitext
Verified Data Provider
Optimized for quick response
bitext Data Products: APIs & Datasets
bitext Pricing & Cost
Dataset Sales Pricing Model
Pre-Built Datasets:
Small Datasets (up to 10,000 entries): $500 - $2,000 per dataset.
Medium Datasets (10,001 to 50,000 entries): $2,500 - $7,500 per dataset.
Large Datasets (50,001+ entries): $8,000 - $20,000 per dataset.
Custom Datasets:
Initial Consultation Fee: $500 (applied towards the final cost).
Custom Dataset Generation: $0.02 - $0.40 per entry, depending on the complexity and specificity of the data requirements.
bitext Reviews
Your Review
There are not enough reviews and ratings for bitext at the moment. Have you worked with bitext? You can help other data professionals better understand bitext’s data products and services by leaving a review now.
bitext Competitors & Alternatives
USA
USA
United Kingdom
USA
About bitext
bitext in a Nutshell
Bitext has been providing NLP/NLG data services to 3 of the top 5 companies on NASDAQ for the last 10 years.
Bitext Automates Text Data Services for Multilingual GenAI. We cover:
-Generation of Synthetic Text, based on proprietary reliable NLG technology (not generative technology)
-Automation of Data Labelling and Annotation (DAL), combining GenAI models and NLP tools with a human-in-the-loop approach
-Verticalization of General-Purpose models (GPT, Mistral…) in 20 domains (Customer Support, Banking, Travel…)
-Training and Evaluation of General-Purpose models (GPT, Mistral…) for conversational AI
Country Coverage
Data Offering
DAL: Automation Tools for Data Annotation and Labelling
We provide custom Data Annotation and Labeling (DAL) services for (Generative) AI. We focus on the automation of human annotation, building custom Human-in-the-loop (HITL) pipelines to improve data annotation speed and quality with custom software applications. A few examples:
Use Cases
Bitext specializes in providing advanced linguistic technology and synthetic data generation to address various industry-specific challenges. Our focus areas encompass a wide range of applications, each tailored to enhance AI and NLP capabilities across different sectors. Here are the primary use cases where Bitext excels:
- Customer Service Automation
Chatbots and Virtual Assistants:
Enhancing chatbot training with high-quality synthetic dialogues.
Improving natural language understanding (NLU) for better customer interactions.
Sentiment Analysis:
Generating labeled datasets to train models for detecting customer sentiment and emotions.
Certifications & Associations
Data Sources & Collection
We use custom and proprietary data sources of linguistic knowledge like ontologies or morphological dictionaries
We use NLP tools, like entity detection or sentiment annotation, to pre-annotate the data for human annotators
We train AI models to perform pre-annotation tasks so human annotators are relieved from mechanical tasks
Key Differentiators
-Proprietary Linguistic Technology: Utilizes advanced algorithms and linguistic expertise to generate synthetic data that is both accurate and contextually rich.
-Customization: Offers highly customizable data solutions tailored to meet specific project and industry requirements.
-Multilingual Support: Provides support for +77 languages, ensuring global applicability and versatility.
-Scalability and Efficiency: Capable of generating large volumes of synthetic data quickly and cost-effectively, making it ideal for extensive model training needs.
-Enhanced Privacy and Security: Ensures data privacy through anonymization and robust security measures, making it compliant with global data protection standards.
Data Privacy
- Special Measures for Data Privacy
Synthetic Data Generation: One of our core offerings is the generation of synthetic data, which is inherently privacy-preserving. Since synthetic data is artificially created and not directly linked to real individuals, it poses no risk to personal privacy.
Integrations
Frequently asked questions about bitext
What does bitext do?
Bitext has been providing NLP/NLG data services to 3 of the top 5 companies on NASDAQ for the last 10 years.
How much does bitext cost?
The supported pricing models for bitext’s data are One-off purchase, Monthly License, and Yearly License. Get talking to a member of the bitext team to receive custom pricing options, information about data subscription fees, and quotes for bitext’s data offering tailored to your use case.
What kind of data does bitext have?
Natural Language Processing (NLP) Data, Machine Learning (ML) Data, Deep Learning (DL) Data, Synthetic Data, and 2 others
What data does bitext offer?
DAL: Automation Tools for Data Annotation and Labelling We provide custom Data Annotation and Labeling (DAL) services for (Generative) AI. We focus on the automation of human annotation, building custom Human-in-the-loop (HITL) pipelines to improve data annotation speed and quality with custom software applications. A few examples:
How does bitext collect data?
We use custom and proprietary data sources of linguistic knowledge like ontologies or morphological dictionaries We use NLP tools, like entity detection or sentiment annotation, to pre-annotate the data for human annotators We train AI models to perform pre-annotation tasks so human annotators are relieved from mechanical tasks
What’s bitext’s data privacy policy?
Special Measures for Data Privacy Synthetic Data Generation: One of our core offerings is the generation of synthetic data, which is inherently privacy-preserving. Since synthetic data is artificially created and not directly linked to real individuals, it poses no risk to personal privacy.
What are the best use cases for bitext’s data?
Bitext specializes in providing advanced linguistic technology and synthetic data generation to address various industry-specific challenges. Our focus areas encompass a wide range of applications, each tailored to enhance AI and NLP capabilities across different sectors. Here are the primary use cases where Bitext excels: Customer Service Automation Chatbots and Virtual Assistants: Enhancing chatbot training with high-quality synthetic dialogues. Improving natural language understanding (NLU) for better customer interactions. Sentiment Analysis: Generating labeled datasets to train models for detecting customer sentiment and emotions.
What platforms is bitext integrated with?
AWS Data Exchange and Databricks Marketplace