When searching for innovative solutions, it is crucial for leaders and decision makers to have the information that allows them to make informed decisions.
Bitext is currently at the forefront of technology since it has been mentioned lately in no less than 20 Gartner reports and was selected as Cool Vendor in AI Core Technologies in 2018. But we keep working hard and Gartner, once again, mentioned Bitext in 4 new Hype Cycle reports.
Bitext: Sample Vendor for Synthetic Data and NLP
Gartner Hype Cycles provide a graphic representation of the maturity and adoption of technologies and applications, and their potential relevance to solve real business problems and exploiting new opportunities.
Gartner Hype Cycle methodology gives you a view of how a technology or application will evolve over time, providing a sound source of insight to manage its deployment within the context of your specific business goals.
Hype Cycles help you separate hype from the real drivers of a technology’s commercial promise, reduce the risk of your technology investment decisions, and compare your understanding of a technology’s business value with the objectivity of experienced IT analysts.
During this summer, Gartner included Bitext, the leading NLP middleware provider, in 4 of its Hype Cycle reports including:
- Hype Cycle for Artificial Intelligence
- Hype Cycle for Enterprise Information Management
- Hype Cycle for Emerging Technologies
- Hype Cycle for Data Science and Machine Learning
In Gartner’s Hype Cycle for Enterprise Information Management, Hype Cycle for Emerging Technologies and Hype Cycle for Data Science and Machine Learning, Gartner mentioned Bitext as a Sample Vendor for Synthetic Data and, in Gartner’s Hype Cycle for Artificial Intelligence Gartner, included Bitext as a Representative Vendor for NLP.
According to Gartner analyst Anthony Mullen, “One of the major problems with AI development today is the burden in obtaining real-world data and labelling (…) Synthetic data addresses the problem of volume and variety for sparse, nonexistent or difficult to get the data“.
He also comments that “Synthetic data can act as a democratizer for smaller players as they try to compete with data-laden tech heavyweights”. Enterprises should expect a rapid growth in the use of these techniques over the next three years.
We believe we have received this recognition because of our relentless focus on product innovation. Our recently launched Bitext Pre-Built Bot Templates accelerate the deployment of new bots by bootstrapping the training process with pre-packaged synthetic data for a wide range of verticals and languages, so customers can have a multilingual bot up and running without effort.
By using synthetic data, our templates offer scalability, modularity, customizability, consistency and high coverage.
In Gartner´s Hype Cycle for Enterprise Information Management, Gartner tells users that NLP offers enterprises significant opportunities to improve operations and services. For many enterprises, the strongest and most immediate use cases for NLP are related to improving customer service (impacting cost, service levels, customer satisfaction and upselling).
Bitext is a vendor with a clear emphasis on linguistics-based abstraction language automation. The Bitext NLP Middleware for bot automated training allows for faster training for bots. After the simplification process, the language generation system produces all possible variants of expressing a simple intent, creating an accurate, automated training corpus for the bot.
Bitext at the forefront of technology
There is no doubt, after all, that Bitext is currently at the forefront of technology since it has been mentioned in no less than 20 Gartner reports in the previous years and was selected as Cool Vendor in AI Core Technologies in 2018. These are some of the latest reports that mention Bitext:
- Boost Your Training Data for Better Machine Learning, 2019.
- Cool Vendors in AI Core Technologies, 2018.
- Market Guide for Text Analytics , 2018.
- Market Guide for Social Analytics Applications, 2018.
- Hype Cycle for Human-Machine Interface, 2018.
- Hype Cycle for Artificial Intelligence, 2018.
- Hype Cycle for the Digital Workplace, 2018.
- Hype Cycle for Human-Machine Interface, 2018.
- Hype Cycle for Mobile Device Technologies, 2018.
- Clarify Strategy and Tactics for AI by Separating Training and ML, 2018.
- Revolutionize Product Information Management by means of Disruptive AI, 2018.
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact.
Gartner disclaims all warranties, express or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.