00:00 Speaker A
Innovative startup deploys AI agents to help raise Series B round of funding, raising $100 million at a $500 million valuation. Joining me now is the leader behind that movement, liser.ai CEO Siva Surendra. Oh Shiva, it’s nice to meet you. Maybe start at a high level for us, Shiva, and explain what the riser does. Well, let’s say I’m a viewer right now. Maybe I’m the CEO, Shiva. There are 100 employees, right? What problem will you solve for me?
00:27 Shiva Surendra
Well, we’re a full-stack agent platform that helps companies automate workflows from HR sales and marketing to all horizontal functions and enterprise functions, but also vertical functions like loan processing at banks and underwriting at insurance companies. So typically the value here is time compression. Can you do a job in 30 minutes that used to take maybe three weeks? So this is agent automation, and you can do it end-to-end on our platform.
01:00 Shiva Surendra
Literally from core functions to corporate functions.
01:04 Speaker A
What are some things that AI agents don’t like, Shiva? Are there certain types of jobs, roles, tasks, etc. that they’re not very good at?
01:12 Shiva Surendra
Yeah, uh, any agent that you think can do the magic of, say, sales. Oh, we felt, oh, we felt like we burned our fingers, so we built AASDR, an agent that can probably sell your products and services to customers. And soon, customers began to expect their meetings to be booked by an agent, but they realized there were many other dependencies. The product must fit the market, the price must match, and there must be customer purchase intent. Therefore, even humans cannot understand it correctly. In short, agents won’t do a good job if it’s closely related to revenue-generating functions or new revenue-generating functions.
