Liquid's models power agentic workflows that make fraud, customer service, and risk functions more streamlined and reliable. Whether running in your data center, at the edge, or in the cloud, they offer low latency and bank-grade privacy at a fraction of frontier-mode costs.
Financial services are practically made for AI solutions. But the data they use isn't.
Financial institutions have a lot to gain from AI adoption, but several issues stand in the way:
Fraud, payment, and trading rely on slow workflows that lack real-time intelligence.
That's why most financial AI deployments never make it past the pilot stage.
Sensitive PII and transaction data remain locked in legacy and on-prem cores.
Because they're hosted entirely on your hardware, Liquid's SLMs are inherently private. When there are no calls to the cloud, there's no public exposure of sensitive data.
Instead of an LLM that does everything, you get a series of small models tuned to do one thing exceptionally well. Trained on your data and protocols, running on your infrastructure, they're designed to solve problems reliably, at a fraction of the cost of cloud-based models.
Smaller, customized models and local processing mean lightning-fast response times. For digital and mobile customers, that responsiveness equals engagement, brand loyalty, and lower churn in the long term.
All of the upsides of true AI integration into financial services, without cloud-based risks.
Liquid's fast, powerful, customized models can supercharge your internal functions—and deliver a best-in-class digital experience to your customers.
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