Rulebase Raises $2.1M to Automate Financial Back Office

Rulebase bets on back-office automation

Y Combinator alum Rulebase announced a $2.1 million pre-seed round led by Bowery Capital, backing a thesis many startups ignore: the next wave of financial services automation will focus on unglamorous but high-value back-office work such as compliance, quality assurance and disputes.

Founded by Gideon Ebose and Chidi Williams — engineers who met in London — Rulebase builds an "agent coworker": an AI agent that reviews customer interactions, flags regulatory risk, and coordinates follow-ups across tools like Zendesk, Jira and Slack while preserving human-in-the-loop oversight.

The company is already in production at customers including business bank Rho and an unnamed Fortune 50 financial institution, and claims improvements that translate directly to lower operational risk and cost.

• Support ticket review and escalation
• Dispute lifecycle management
• Quality assurance and compliance checks

Where traditional QA teams sample 3–5% of interactions, Rulebase evaluates 100% and reports cost reductions of up to 70% and escalation drops — Rho saw up to 30% fewer escalations in some workflows.

The founders bring deep industry and product experience — Ebose from Microsoft product and Williams from Goldman Sachs engineering — and say the product-market fit emerged from watching fragmented, manual regulatory workflows slow down both startups and incumbents.

Rulebase's business model is usage-based: customers pay per interaction reviewed or workflow automated. The startup is focused on precision-heavy financial verticals — business banks, neobanks and card issuers — across Africa, Europe and the U.S., with insurance and other adjacent areas on the roadmap.

• Fraud investigation automation
• Audit preparation and evidence aggregation
• Regulatory reporting and timeline tracking

Investors and customers are betting on domain-specific AI that understands MasterCard rules, CFPB timelines and other regulatory nuance. That specificity is Rulebase’s competitive moat: automation in finance must be exact, explainable and auditable.

What this means for financial operators

For banks and fintechs wrestling with expensive, error-prone manual processes, Rulebase points to a pragmatic automation path: focus first on high-volume compliance and QA tasks, prove cost and risk improvements, then expand into adjacent workflows. Integration across existing ticketing and collaboration tools keeps the human team in control.

QuarkyByte’s approach would be to help organizations map those fragmented touchpoints, quantify the compliance and cost upside, and design pilot integrations that validate assumptions quickly. With careful rule-mapping and measurable KPIs, firms can convert back-office drudgery into a competitive advantage.

Rulebase’s raise and early traction illustrate a broader lesson for AI in finance: the biggest near-term wins may not be shiny chat interfaces but the dusty, compliance-heavy workflows that cost firms time and money. Start small, measure hard, and scale where the rules and ROI are clear.