Gradient Labs gives every bank customer an AI account manager

In banking, resolving a customer issue is rarely simple. Cases like fraud or blocked payments require strict adherence to complex procedures across multiple teams. When systems fall short, customers are passed between teams, wait in queues, and face delays at moments when the stakes are highest.

Gradient Labs ⁠ (opens in a new window) is built to handle this complexity. The London-based company is building AI agents that give every bank customer the experience of a dedicated account manager. Founded by a team that previously led AI and data efforts at Monzo, the company’s platform is built on OpenAI models and is now shifting production traffic onto GPT‑5.4 mini and nano.

“We’re seeing 500-millisecond latency with GPT‑5.4 mini and nano, which is exactly what we need for natural voice conversations,” says Danai Antoniou, Co-Founder and Chief Scientist at Gradient Labs. “We’re moving a significant portion of our workload over.”

This result shaped how Gradient Labs designed its system. The team built a hybrid architecture that uses OpenAI models for reasoning-intensive steps and smaller models for faster, deterministic tasks, with routing that adapts based on complexity and latency constraints.

Financial institutions don’t deploy systems like this on faith. They need to see, step-by-step, that it behaves correctly under real-world conditions.

Gradient Labs also gives teams control over how the system is introduced. They analyze historical support data to map out the types of customer issues a bank handles and how often they occur. Teams can then choose which categories the AI should handle, starting with lower-risk workflows and expanding over time.

That impact is reflected in the company’s growth. Gradient Labs has increased revenue more than 10x over the past year, expanding from inbound support into outbound and back-office processes.

In banking, customer interactions are governed by standard operating procedures (SOPs) that define what should happen at each step.

The system verifies their identity, handling corrections and interruptions in real time.

It answers follow-up questions, such as delivery timing, and suggests next steps.