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Y Combinator-backed Rulebase wants to be the AI coworker for fintech

From TechCrunch

By Tage Kene-Okafor

September 16, 2025

Y Combinator-backed Rulebase wants to be the AI coworker for fintech

Y Combinator-backed Rulebase wants to be the AI coworker for fintech

Y Combinator-alum Rulebase is betting that the next wave of automation in financial services won’t be about flashy AI interfaces, but the unglamorous back-office tasks like compliance.

The startup, founded by Gideon Ebose and Chidi Williams, two Nigerian engineers who met in London, just raised a $2.1 million pre-seed round led by Bowery Capital, with participation from Y Combinator, Commerce Ventures, Transpose Platform VC, alongside several angels.

Financial services firms spend enormous amounts of effort on support tickets, resolving disputes, ensuring quality assurance, and regulatory compliance. Rulebase’s software, which it calls an agent coworker, replaces much of the manual grunt work in these tasks. Its AI agent can evaluate customer interactions, flag regulatory risks, and trigger the right follow-ups across tools like Zendesk, Jira, and Slack without losing the human-in-the-loop oversight that financial firms demand.

“Our ‘Coworker’ tool integrates across platforms and collaborates with human agents and back-office teams to fully manage the dispute lifecycle while saving time, reducing errors, and maintaining compliance,” said CTO Williams. Currently, the year-old startup is already deployed at customers like U.S. business banking platform Rho and an unnamed Fortune 50 financial institution.

Rulebase wasn’t the founders’ first swing. Ebose, a former product lead at Microsoft and Williams, a former backend engineer at Goldman Sachs, built several products together like an AI customer feedback tool before eventually settling on Rulebase. The idea came about after seeing how inefficient back-office operations were in small and large financial institutions, especially when it came to regulatory workflows.

The startup currently focuses on workflows triggered by customer service interactions, with its first wedge around quality assurance. QA analysts in traditional financial institutions typically manually review 3–5% of support interactions to ensure reps follow compliance protocols. 

For the love of God, stop calling your AI a co-worker

Rulebase now evaluates 100% of such interactions, cutting costs by up to 70%, the founders say. In the case of Rho, for instance, Rulebase has helped cut escalations by up to 30%.

“We automate workflows that start with a customer interaction, areas we’re already great at handling end-to-end,” CEO Ebose said in an interview with TechCrunch. “While much of that is QA, compliance, and disputes tied to customer calls and messages, long-term our goal is to take on as many manual back-office tasks as possible by pulling these fragmented steps and tabs into one coordinated workflow.”

The new funding will help it double down on engineering and eventually add new features to AI Coworker like fraud investigation, audit preparation, and regulatory reporting.

Rulebase is focused on financial services for now because automation demands precision. “You need to understand MasterCard’s rules, CFPB timelines. That depth of domain knowledge is our moat,” Ebose said.

They company is targeting business banks, neobanks, and card issuers across Africa, Europe, and the U.S. But the roadmap could eventually include adjacent verticals like insurance, where similar workflows exist.

Screenshot

Revenue is growing fast, with “double-digit” month-over-month growth since joining Y Combinator’s Fall 2024 batch, the founders say. Rulebase’s business model is usage-based, charging per interaction reviewed or workflow automated.

As one of the few African founders to get into YC building AI tools, Ebose and Williams’ advice to founders trying to get accepted into the global accelerator is to think globally from day one.

“We’re in a moment where small teams can deliver more value, more quickly, than ever before, so limiting yourself to ‘X for Y’ or a narrow vertical feels like a missed opportunity,” Williams remarked. “With AI, it feels obvious that you have to go after something massive. Anything less than the most ambitious version of your idea likely won’t cut it,” said Williams, who before Rulebase built Buzz, an early open-source speech-to-text tool with over 300,000 downloads and over 12,000 GitHub stars.

View original article on techcrunch.com

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