Here's one of many stories of how some of the fastest-growing fintechs use @RulebaseHQ to scale their customer operations. A year ago, Rho reviewed only a tiny fraction of customer interactions by hand and caught issues weeks late. Today, Rulebase reviews 100% of interactions across phone, email, and chat in real time, then acts on what it finds. When an interaction shows a customer at risk, a repeat contact, or an SLA about to slip, a Rulebase agent picks it up, loops in the owning team, and follows through to resolution. The results: 4x more issues caught, 3x fewer escalations, and ~90% less manual review.

New website: rulebase.co. Thanks to all our customers and partners.

We launched Revenue on @RulebaseHQ today to help fast-growing fintechs onboard more customers and merchants. Our agents connect with your existing tools to run end-to-end onboarding: collecting and following up on missing documents, reactivating dormant accounts, and much more across voice, email, SMS, WhatsApp and more!

Excited to share that we raised $2.1M to build the future of CX and back-office operations in financial services. For fintechs and banks, customer service back-office work remains a maze of manual processes, including quality assurance, dispute investigations, and fraud and compliance checks. At @RulebaseHQ, we built Coworker to work alongside CX and ops teams to: - Review 100% of interactions for compliance and quality assurance - Automatically file and track fraud and dispute cases end-to-end across CX, case management, and back-office platforms - Proactively follow up with teammates and third-party partners to keep SLAs on track - Flag compliance risks in real time and generate audit-ready reports. Coworker bridges CX and back-office ops, automating the most manual tasks so nothing slips through the cracks and every customer issue is resolved quicker and more effectively. A massive thank you to our investors, customers, and the growing @RulebaseHQ team for believing in our vision and being part of this journey! Our round was led by @LorenStraub from @BoweryCapital, with participation from @ycombinator, @CommerceVC, @transposevc, and founders of t3 chat, Atrium, Cron (now Notion Calendar): @theo, @raphaelschaad, and more. Incredibly grateful to have the support of the @ycombinator community and mentors, @dflieb and @koomen. Thank you all for being incredible partners on this journey!

I'd love to speak with customer services/fraud teams at fintechs. We'll work with you closely to match the risk models and scoring to your specific needs and use cases. Contact me directly at cal.com/chidi-rulebaseco/30m….

After the call, we generate an in-depth report on all flagged calls for the fraud team to investigate further. In the video, I show an example of a malicious caller using a VoIP system to change a customer's details. But Radar works for many other scenarios involving attacks on customer services.

During the call, we run a real-time analysis of voice and behavioural characteristics: - Does the call match a known fraud script? - Is the caller using stolen info to take over a customer's account? - Does the voice match a sample previously added to a watchlist?

Before the agent even answers the incoming call, we run checks on the phone number and caller network: - Has a customer called with this phone number before? - Is this number registered to a suspicious VoIP rather than a real mobile network?

Introducing Radar, @RulebaseHQ's fraud copilot for customer service teams: Radar integrates with your customer service tools, such as Zendesk and Intercom, to provide agents with real-time fraud risk information before, during, and after incoming conversations.