If you are asking how to build a multi-agent AI system, you’ve probably hit the limits of off-the-shelf tools like ChatGPT or Perplexity Finance that can’t execute multi-step decisions across teams, tools, and data silos. Most likely, you want to automate complex, regulated workflows, but are unsure if your in-house team knows how to design, secure, integrate and scale them.

But a multi-agent system isn’t the answer for every financial services use case. 

As an AI-enablement company with experience implementing over 100 custom AI solutions across banking, insurance, and wealth, we know when a multi-agent system makes sense. In this article, we’ll help you understand if a multi-agent system is the right choice and how to design one with a secure, scalable architecture.