Eloquent AI Closes $7.4M Seed in 3 Days to Automate 96% of Financial Services Customer Operations

Eloquent AI raises $7.4m to automate financial services customer support

Eloquent AI has launched its AI Operator platform and closed a $7.4 million seed round. The round was led by Foundation Capital with participation from EJF Ventures, Duke Capital Partners, Zeno Ventures, and Y Combinator. It closed in three days and was 12x oversubscribed.

Founded by entrepreneur Tugce Bulut and machine learning professor Dr. Aldo Lipani, the company is focused on automating customer operations for regulated financial institutions. The platform aims to move beyond FAQ-bound chatbots and handle full workflows end-to-end with auditability and compliance.

What the AI Operator does

The platform is powered by Oratio, a proprietary multimodal LLM trained on regulated financial workflows. Eloquent AI says Operators observe how human agents work across internal systems via browser control and computer vision, then mirror those actions-no APIs, prompting, or engineering work required.

Use cases include fraud investigations, dispute resolution, and KYC/AML reviews. The company claims financial institutions can automate up to 96% of customer operations, cutting costs, speeding response times, and improving accuracy.

How teams would use it

CX teams "show" the Operator how tasks are done by explaining steps in natural language or demonstrating on-screen. The Operator learns the workflow and executes it independently, moving through internal tools the way a human would.

This approach keeps institutional logic intact and preserves audit trails across systems. It's built for regulated environments where precision and traceability matter.

Why this matters for CX leaders

Support teams in financial services face rising volume, strict compliance, and shrinking headcount. Automating full workflows-not just replies-unlocks meaningful gains in average handle time, first contact resolution, and back-office capacity.

"We're finding the cliché of financial institutions being laggards in tech adoption to be substantially overstated," says Bulut. "These organisations are often overwhelmed with compliance requirements and backlogged customer ops. The desire to address these issues is certainly there, it's just that, until now, the solution hasn't been."

Practical next steps for Customer Support leaders

• Shortlist high-friction workflows: fraud claims, disputes, KYC refresh, chargebacks, account recovery.
• Define success metrics upfront: AHT, FCR, backlog reduction, QA accuracy, audit exceptions.
• Run a contained pilot: 1-2 workflows, limited access, daily QA sampling, clear rollback plan.
• Map controls and logs: evidence capture, decision trails, approval gates, model change management.
• Keep humans in the loop for edge cases and high-risk actions; route exceptions by policy.
• Align early with risk, compliance, and IT on data access, credentials, and monitoring.

Funding snapshot

Seed: $7.4m led by Foundation Capital; participants include EJF Ventures, Duke Capital Partners, Zeno Ventures, and Y Combinator. The round was 12x oversubscribed and closed in three days-signal of demand for operations-grade AI in financial services.

Further resources

• Practical AI tools for finance to benchmark options and stack components.