Workforce Management Featured Article
Gnani.ai Helps Customer-Face Companies Bridge the Digital Divide
Though digitization and internet technologies have brought humans closer to machines, the need to bridge the communication barrier between them will shape its future, according to natural language processing and artificial intelligence company Gnani.ai.
“The demand for automation and analytics for digital transformation has increased rapidly since the start of the pandemic in 2020, Ganesh Gopalan, cofounder and CEO of Gnani.ai told TechStory. “In addition, in addition, we are building a robust product roadmap and taking the SaaS (News - Alert) route to the market to enable our customers to use the platform on a self-serve basis.”
The idea is that highly complex natural language processing technologies and AI can be out of reach to companies that lack the deep IT resources that are required to use them. Gnani.ai builds products for vertical industries such as BFSI, healthcare, automotive and more. These products are built on the software-as-a-service (SaaS) model.
“The demand for automation and analytics for digital transformation has increased rapidly since the start of the pandemic in 2020,” said Gopalan in the TechStory interview. “In addition, we are building a robust product roadmap and taking the SaaS route to the market to enable our customers to use the platform on a self-serve basis.”
The products built by Gnani.ai has allowed its customers to expedite their projects involving digital transformation to adapt quickly to this “new normal.” Products that help with digital transformation are taking the pressure off human agents and allowing them to automate the tasks required to help customers in live calls, and also helping customers to help themselves. It’s important technology to help companies that have experienced a decline in speed and quality of customer support during the pandemic.
“This is primarily since agent availability during the pandemic became a challenge plus routine customer service processes do not need human intervention,” said Gopalan. “Also, AI and ML are making bots more intelligent due to continuous learning and training. The number of inbound leads and subsequent deployment that we have done in the last few months have been extraordinary. Use cases involving voice-led omnichannel automation and analytics for multiple industries across multiple channels have gained traction.”
Edited by Luke Bellos
