Kastle Raises $24 Million to Help Lenders Adopt Agentic AI

Kastle, an agentic AI platform for consumer lenders, has raised $24 million in new funding.

The company’s Series A round, announced last week and led by Insight Partners, will help Kastle expand its engineering, product and go-to-market teams, deepen its platforms’ capabilities and accelerate deployments with financial institutions.

“AI has given financial institutions a historic opportunity to transform how that work gets done,” Kastle said in a news release. 

“But for most large enterprises, the path to adoption is logistically challenging. Replacing legacy infrastructure with an entirely AI-native technology stack could require years of complex, high-risk migration, in a world where technology shifts happen every other quarter, and layering conventional AI assistants onto existing systems captures only a fraction of AI’s potential.”

Kastle argues this has led to an adoption gap, with lenders recognizing AI’s potential but limited by their systems and operating models. The company says its platform remedies this with its platform, which lets financial institutions to deploy specialized artificial intelligence (AI) agents handle “high-volume, repeatable work,” while human workers concentrate on complicated cases where “judgment, expertise, empathy, and relationships” are required.

“For years, enterprises have effectively been presented with a false choice: accept the limitations of legacy operations or endure a long and risky replacement of the systems at the heart of their business,” said Rishi Choudhary, Kastle’s co-founder and CEO.

“Kastle creates a third path. We give financial institutions an AI workforce that can operate across the systems they already have, so they can capture the benefits of AI now, not five years from now.”

In other agentic AI news, PYMNTS looked at the technology’s role in combatting financial crime last week in an interview with Christopher Phillips, director of financial crime industry engagement at Flagright.

AI agents, that report said, can offer banks something their existing financial crime operations have trouble producing: consistent, well-documented and routinely audited investigations.

“The AI doesn’t get bored. It doesn’t get fatigued. It doesn’t forget to include that link for the one search it did,” Phillips said. The result, he added, can be “a robust output that is easy to audit.”

While traditional financial crime monitors quality assurance mainly largely through sampling a relevant percentage of cases to extrapolate findings across the larger program, agentic AI makes another model possible, the report said.

“With AI, you can do all of them,” Phillips told PYMNTS. “You could literally do a QA or an audit of every single case.”