Agentic AI helps AUM Biotech punch above its weight

AUM Biotech needs to do a lot with a little. Agentic AI is helping it fill the gaps.

The Philadelphia-based startup, which specializes in genetic research tools for gene silencing and regulation, has fewer than 10 employees, but it has global customers, including some of the world’s biggest pharmaceutical companies.

“We provide biomedical scientists with gene manipulation or regulation products that can help them understand the biology of a disease,” says AUM Biotech founder and CEO Veenu Aishwarya, who specialized in cancer research at UPenn’s Perelman School of Medicine after emigrating from India in 2009. “And we’re shipping to 37 or 38 countries right now, working weird hours in different time zones.”

AUM Biotech isn’t venture-backed. Its funding depends entirely on sales, so with a small staff, reaching out to new customers, keeping in touch with existing customers, and providing scientists with customer support on demand — all requirements to keep sales flowing — has been challenging.

“Being a small company with limited resources, you have to figure out a way to optimize things,” he says.

That’s where agentic AI and Salesforce Agentforce play a key role by automating many of the company’s internal processes, like customer support.

A solution within reach

Simply put, Aishwarya is AUM Biotech’s IT department. After seeing Salesforce co-founder, chairman, and CEO Marc Benioff talk about AI agents on CNBC last year, Aishwarya was inspired to dig into what the new technology could do for his business.

“I’m not a coder, I’m a cancer researcher,” he says. “But for the past several months, I’ve drawn myself into learning through YouTube and Google.”

AUM Biotech was already using Salesforce for its CRM and Salesforce Data Cloud to manage and govern its data, so much of the hard work around data hygiene to get agentic AI off the ground was already done. And within a month, he deployed Agentforce SDR (sales development representative), an autonomous agent to scale top of funnel efforts, streamline prospect qualification, and generate a 24/7 pipeline.

“You can reach out to people, and after the first few interactions, once they’re ready, it can be transferred to a human agent, who can close the deal or have further interactions,” Aishwarya says. But the first agent took time to deploy because of what needed to be learned, but deployments of subsequent agents have gone much faster.

Put into practice

The company is using AI to record and summarize meetings, which an agent can use to personalize emails to customers. Aishwarya has also created a web agent to answer product questions on the company’s website, though he says it can also transfer visitors to a human representative if necessary.

“The information also gets captured in our Salesforce environment,” he says. “If it’s an existing client, my salesperson knows they were on the website. If it’s a new client, that becomes a new lead.”

He’s also eagerly awaiting the release of agents capable of voice.

“Hopefully, one day soon, customers can just call us, and we can have agents do Q&A with voice, which will be even simpler,” he says, adding that he can deploy these features with confidence because Data Cloud enables strict data governance. That’s not only important to his company, but to its clients, who often need to share valuable and confidential data.

“We want to make sure data isn’t getting sucked up by AI and used as training data,” he says.

In all, Aishwarya says agentic AI is helping his company reach out to thousands of people every week while providing existing customers with rapid responses to their queries.

“We’re saving time, and timesaving is the most important thing a small company can do,” he says. “I can’t wait to see what the next few months and years will look like.”