Gradient Labs, a London-based company, has secured $13m in a Series A funding round aimed at automating customer operations within the financial services sector.
The funding was spearheaded by Redpoint Ventures, with additional investments from Exceptional Capital, Liquid 2, LocalGlobe, Puzzle Ventures, among others.
Founded in 2023, Gradient Labs has developed what it claims is the first compliant artificial intelligence (AI) platform specifically designed for the financial services industry.
The company asserts that while most customer experience (CX) AI solutions address the visible aspects such as chat and call interactions, Gradient Labs automates underlying operational processes.
These include document processing, fraud and sanctions screening, and supporting customers in vulnerable situations. Such processes are often where customer experiences encounter issues, according to the firm.
Gradient Labs CEO Dimitri Masin, in a blogpost, wrote: “We’re rapidly expanding our platform, going beyond the tasks a generalist hire could execute with a standard operating procedure (SOP).
“We’re building AI that doesn’t just follow scripts, but makes the nuanced decisions that today are reserved for highly trained specialists. The kind of complex decision-making required in money laundering investigations, technical troubleshooting, and nuanced compliance scenarios.”
Gradient Labs launched its AI agent in November 2024 and has since partnered with several European fintech companies, including Plum, Zego, Lendable, Yonder, Nala, and Sling.
Notably, the company achieved the milestone of deploying the first live autonomous AI customer support for a major regulated UK bank.
The latest injection of capital is expected to facilitate Gradient Labs’ expansion into the US market and enhance their platform’s capabilities beyond standard operating procedures. The company aims to develop AI capable of making complex decisions usually handled by specialists in areas such as money laundering investigations and technical troubleshooting.
