Yellow.ai, a leading enterprise-grade Conversational Artificial Intelligence (AI) platform trusted by 1000+ enterprises globally, has announced the launch of its proprietary DynamicNLP™, a first in the enterprise Conversational AI space to enable enterprises to go live within minutes with lower operational costs and an intent accuracy of over 97%.
According to the future of conversational AI from Deloitte, training AI agents with manual methods can take as long as six to nine months, making it one of the most common setup challenges faced by enterprises. Yellow.ai DynamicNLP™ eliminates the tedious process of training and labelling Natural Language Processing (NLP) models manually. This enables
Dynamic AI agents to learn on the fly, helping enterprises to set up Conversational AI flows within minutes, and reduce training data-related costs and efforts. Yellow.ai DynamicNLP™ comes with a pre-trained model built using billions of anonymized conversations, which helps in the reduction of unidentified utterances by up to 60%, making the AI agents more human-like and scalable across industries with wider use-cases.
“Yellow.ai DynamicNLP™ is a first of its kind proprietary technology in the global enterprise Conversational AI industry—a breakthrough innovation that can help enterprises save time, effort and operational cost while accelerating their go-live strategy,” Raghu Ravinutala, Co-Founder of and CEO at Yellow.ai. “It enables our pre-trained Dynamic AI agents to deliver superlative moments of truth across the entirety of customers’ and employees’ lifecycles. As global tech innovators, we see our DynamicNLP™ as a significant step forward in realising the true potential of NLP as a game-changing technology.”
Eric Hansen, CIO at Waste Connections, said “Yellow.ai has helped us accelerate our AI automation journey for some of the most important use cases, and the launch of DynamicNLP™, which enables zero training for NLP models, would elevate customer and employee experiences from day one. We firmly believe that Yellow.ai DynamicNLP™ will open new avenues to scale up additional use cases of customer support and agent productivity.”
With DynamicNLP™, Yellow.ai’s platform is capable of improving the accuracy of seen and unseen intents in utterances right from day one. The elimination of manual labeling also helps remove the errors propagated, leading to a stronger, more robust NLP with better intent coverage for all types of conversations. With the agility offered by Yellow.ai DynamicNLP™, enterprises can successfully maximise efficiency and effectiveness across a wider gamut of use cases, including Customer Support, Customer Engagement, Conversational Commerce, HR and ITSM Automation.
Archive
- October 2024(44)
- September 2024(94)
- August 2024(100)
- July 2024(99)
- June 2024(126)
- May 2024(155)
- April 2024(123)
- March 2024(112)
- February 2024(109)
- January 2024(95)
- December 2023(56)
- November 2023(86)
- October 2023(97)
- September 2023(89)
- August 2023(101)
- July 2023(104)
- June 2023(113)
- May 2023(103)
- April 2023(93)
- March 2023(129)
- February 2023(77)
- January 2023(91)
- December 2022(90)
- November 2022(125)
- October 2022(117)
- September 2022(137)
- August 2022(119)
- July 2022(99)
- June 2022(128)
- May 2022(112)
- April 2022(108)
- March 2022(121)
- February 2022(93)
- January 2022(110)
- December 2021(92)
- November 2021(107)
- October 2021(101)
- September 2021(81)
- August 2021(74)
- July 2021(78)
- June 2021(92)
- May 2021(67)
- April 2021(79)
- March 2021(79)
- February 2021(58)
- January 2021(55)
- December 2020(56)
- November 2020(59)
- October 2020(78)
- September 2020(72)
- August 2020(64)
- July 2020(71)
- June 2020(74)
- May 2020(50)
- April 2020(71)
- March 2020(71)
- February 2020(58)
- January 2020(62)
- December 2019(57)
- November 2019(64)
- October 2019(25)
- September 2019(24)
- August 2019(14)
- July 2019(23)
- June 2019(54)
- May 2019(82)
- April 2019(76)
- March 2019(71)
- February 2019(67)
- January 2019(75)
- December 2018(44)
- November 2018(47)
- October 2018(74)
- September 2018(54)
- August 2018(61)
- July 2018(72)
- June 2018(62)
- May 2018(62)
- April 2018(73)
- March 2018(76)
- February 2018(8)
- January 2018(7)
- December 2017(6)
- November 2017(8)
- October 2017(3)
- September 2017(4)
- August 2017(4)
- July 2017(2)
- June 2017(5)
- May 2017(6)
- April 2017(11)
- March 2017(8)
- February 2017(16)
- January 2017(10)
- December 2016(12)
- November 2016(20)
- October 2016(7)
- September 2016(102)
- August 2016(168)
- July 2016(141)
- June 2016(149)
- May 2016(117)
- April 2016(59)
- March 2016(85)
- February 2016(153)
- December 2015(150)