Breaking Customer Service Silos With Fin AI Agents

Breaking Customer Service Silos With Fin AI Agents

What would change if a customer could return three days later through a different channel and continue the same conversation without repeating a single detail?

In this episode of Tech Talks Daily, I speak with Paul Adams, Chief Product Officer at Fin, the company previously known as Intercom. Paul has spent almost 13 years with the business and provides a candid account of how it abandoned its previous roadmap, placed a company-wide bet on AI, and rebuilt its products and working practices around AI agents.

Our conversation begins with Fin's move from a customer service agent toward what Paul calls a single customer agent. The idea is that customers do not care whether their request belongs to sales, service, or customer success. They want the company to understand their situation and help them complete the task.

Paul explains how AI agents can bring customer history, company knowledge, operational data, and business goals into the same conversation. This could allow an agent to resolve an issue, support a purchase, recognize a valuable customer, or transfer the conversation to a human without losing the context already provided.

We also examine the economics behind poor customer service. Many companies are not ignoring customers through a lack of concern. They are receiving volumes of requests that cannot economically be handled by adding people alone. Paul says some Fin customers are resolving between 70 and 90 percent of customer queries through AI. Rather than seeing entire teams disappear, he is observing employees move into customer success, knowledge management, AI supervision, and higher-touch services.

The episode also provides an unusually candid account of what it took to rebuild an established SaaS company around AI. Paul describes the process as brutal. Strategies were discarded, familiar processes were removed, and some people decided the new direction was not for them. His advice is to prioritize speed, place smaller experiments in front of real customers, and learn from evidence rather than waiting for every internal condition to become perfect.

Paul also recalls working on early versions of mobile YouTube and Gmail when colleagues questioned whether anyone would watch video or answer email on a phone. Those stories provide a timely warning about judging new technology by its early limitations.

Could AI agents finally give customers continuity across sales, service, and support, or will internal company structures remain the greater obstacle? Listen to the conversation and share your thoughts with me.

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