[24]7 AIVA: This new virtual agent uses both text & speech to answer queries

[24]7 AIVA uses artificial intelligence to break down the siloes between channels, empowering businesses to deliver enhanced automation

[24]7 AIVA


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[24]7 AIVA ia new AI-powered Virtual Agent that is built for both self-service and assisted channels to help enterprises provide a a more personalized, predictive and effortless customer experience.

Built by intent-driven customer experience solutions provider [24]7, the new virtual agent uses artificial intelligence to break down the siloes between channels, empowering businesses to deliver enhanced automation that results in faster resolution of consumer queries. With a common language and intent model across speech and digital channels, [24]7 AIVA can be built once and deployed anywhere, including web, IVR, messaging platforms (e.g. Apple Business Chat and Facebook Messenger), and SMS.

“We’ve designed AIVA to perform as well as a company’s best human agent,” said Scott Horn, Chief Marketing Officer of [24]7.

“With [24]7 AIVA, businesses can predict what customers are looking to do, and deliver the best resolution. Consumers can begin a conversation through self-service, and complete the transaction with a live chat agent who has context of the previous conversation. The ability to use channels interchangeably, pick up where they left off, and never have to start over, results in a superior customer experience.”

Read More: The bot saga: Are they the new human substitutes?

[24]7 AIVA enables intelligent, two-way interactions for both voice and text channels, and features the following capabilities:

Single Language and Intent Model Across Channels – Using the same language intent model across speech and digital channels means that all interactions draw from the same business logic, application logic and back-end integration capabilities with enterprise systems (e.g. CRM, billing systems).

Ability to Understand Vague Intents – Since humans often communicate in vague terms, the ability to understand consumer intent is critical. For example, when a consumer calls a phone company and says “I hate my phone,” AIVA can understand that the consumer is frustrated, and may be looking for a new device.

Conversational Design – [24]7 AIVA is built on Microsoft Deep Neural Network technology. This improves recognition of native speakers by two to four points, and for non-native English speakers by up to 26 percent over traditional natural language solutions.

Continuous Improvement – Using advanced machine learning techniques, AIVA improves consumer interactions based on real-world voice and digital interactions. This results in the unique ability to learn over time, and emulate the practices of a company’s best human agent.

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