Your Multilingual NLP Middleware

Chatbots & Virtual Assistants

Build a multilingual, automated CS chatbot with 90% understanding accuracy

NLP Solutions for AI Engines

Build the most accurate multilingual NLP infrastructure for your AI engine 

Customer Experience (CX)

Get insights into what your international customers say about your company with 90% 

Techcrunch Case Study

Lemmatization

Automotive Industry Case Study

Chatbots & Virtual Assistants

Build a multilingual, automated CS chatbot with 90% understanding accuracy

Techcrunch Case Study

NLP Solutions for AI Engines

Build the most accurate multilingual NLP infrastructure for your AI engine 

Lemmatization

Customer Experience (CX)

Get insights into what your international customers say about your company with 90% 

Automotive Industry Case Study

Multilingual Approach

More than 100 languages and variants available

Multilingual Approach

More than 100 languages and variants available

“With its suite of capabilities [NLP Middleware], Bitext can improve the performance of almost any conversational engine and project.”

Bitext, AI Core Technologies Cool Vendor 2018

“With its suite of capabilities [NLP Middleware], Bitext can improve the performance of almost any conversational engine and project.”

Bitext, AI Core Technologies Cool Vendor 2018

Improving Rasa’s results by 30% with artificial training data: Part II

Increasing bot accuracy has never been so easy. How? Generating artificial training data, not manually, but using auto-generated query variations. We have benchmarked Rasa and other platforms, and their accuracy comes up to 93% thanks to Bitext artificial training data tech.

Improving Rasa’s results with artificial training data. Part I

Rasa, as other chatbot platforms, still relies on manually written, selected and tagged query datasets. This is a time-consuming and error-prone process, hardly scalable or adaptable.

improving-rasas-results-with-artificial-training-data-ii

Improving Rasa’s results by 30% with artificial training data: Part II

Increasing bot accuracy has never been so easy. How? Generating artificial training data, not manually, but using auto-generated query variations. We have benchmarked Rasa and other platforms, and their accuracy comes up to 93% thanks to Bitext artificial training data tech.

improving-rasas-results-with-linguistics-based-nlg

Improving Rasa’s results with artificial training data. Part I

Rasa, as other chatbot platforms, still relies on manually written, selected and tagged query datasets. This is a time-consuming and error-prone process, hardly scalable or adaptable.

Success Stories

Working with 3 of the Top 5 largest companies in NASDAQ

Working with 3 of the Top 5 largest companies in NASDAQ

Worldwide Language Coverage

Need More Info?

At Bitext, we focus on linguistic-based language automation to deliver innovative customer experiences. If you want to test our solutions or learn more, we recommend you schedule a personalized demo from one of our experts.

Request a Demo

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