00:00 Speaker A
An innovative startup just deployed an AI agent to help fund raise for its series B round where they raised $100 million at a $500 million valuation. Joining me now is the leader behind that move, Siva Surendra, liser.ai CEO. Uh Siva, it is great to see you. Maybe start broadly for us, Siva, just explain what what uh what liser does. You know, let let’s say I’m I’m a viewer right now. Maybe I’m a CEO, Siva. I got 100 employees, right? What what problem are you solving for me?
00:27 Siva Surendra
Yeah, we are uh full stack agent platform that helps uh enterprises to automate workflows right from say sales and marketing in HR, all the horizontal functions, corporate functions, but also vertical functions like loan processing in a bank or underwriting for an insurance firm. So typically the value here is time compression. Can you get a job done in 30 minutes that probably took you three weeks previously? So uh so that’s the agentic automation and you could do that on our platform end-to- end
01:00 Siva Surendra
uh all the way from literally the core functions to even the corporate functions.
01:04 Speaker A
What are AI agents uh maybe not good at, Siva? Like is there certain kinds of work or roles or or tasks they’re they’re not as well suited for?
01:12 Siva Surendra
Yeah, uh any agent that uh you think could do magic, uh for example, selling. Uh we’ve we’ve felt uh we’ve uh burnt our fingers firsthand where we built an AASDR, an agent that can probably sell your product or service to a customer. And very soon we realized that uh the customer started expecting uh meetings to be booked by the agent, but that it had a lot of other dependencies. Your there should be product market fit, your pricing should uh match, there should be a customer intent to buy and all of that. So which even humans cannot get it right. So, long story short, anything that’s uh uh say closely related to revenue generating function, new revenue generating function, the agents don’t do a good job.