I firmly believe that the introduction of LLMs will be as essential to the future of human-computer interaction as the introduction of the mouse and keyboard were. Every technology company with sufficient resources should be exploring the implications of LLMs on their business.
Most of our research for LLMs falls into three buckets:
1) Internal processes – Any area where an employee is writing or reading some kind of communication is up for grabs.
2) Developer productivity – Whether it's improving the quality of code, reducing time to implementation, or answering questions about our services and architecture... empowering our eng team with LLMs is an area of major interest.
3) Customer Experience – Employees frequently need to write memos for expenses or have questions about Travel & Expense policies (e.g. "Can I buy alcohol at this team dinner?").
We're, of course, exploring far more interesting use cases than just what's above, but that's the low hanging fruit.
LLMs are valuable to all companies of any significant size, just for knowledge management. Then for a bank specifically, there a ton of text classification and summarization tasks when it comes to expense management, bill pay and all the other services they offer. There's also internal stuff. Fraud and KYC would be helped a lot.
To answer your question though, Brex uses AI for a lot of things some of which being:
1. Fraud/Risk/Underwriting
2. Auto-generated receipts and data enrichment
3. AI assistants for all users that have a ton of capabilities
There's a lot more as well but these are just some of the obvious ones.
But at least this isn't a product they would expect to make the majority of their money from since Brex makes its money elsewhere and can afford to waste it on gimmicks and experiments like this.
Unlike the thousands of new so-called AI startups which are just a thin wrapper around OpenAI's API and have no moat.