Kasisto, the market leader for AI in banking, has officially announced the launch of KAIgentic, which happens to be an agentic AI platform purpose built for banking.
According to certain reports, the stated platform arrives on the scene bearing the means to conceive an AI archetype that thinks like a bank’s best banker. More on same would reveal how KAIgentic effectively combines intelligence, compliance, and bank grade performance in one platform across customer experience, employee experience, and AI operations.
Not just that, the technology can also birth autonomous AI agents capable of delivering intelligent, personalized, and proactive experiences across voice and digital channels, while simultaneously meeting strict regulatory and risk management requirements.
To understand the significance of such a development, we must take into account how many banks and credit unions actually experiment with generic large language models and untested agent frameworks. Against that,; KAIgentic brings to their disposal secure, auditable, domain specific AI agents that, on their part, are deeply embedded within the systems currently supporting the banking sector.
“Trust is the currency of banking, and most AI cannot be trusted,” said Lance Berks, CEO of Kasisto. “KAIgentic changes that. It is not a prototype or a pilot. It is production ready, compliant by design, and built to operate inside the real world systems banks rely on every day.”
Talk about the whole value proposition on a slightly deeper level, we begin from the promise of an end-to-end compliance architecture, which includes integrated controls for fraud detection, audit logging, policy enforcement, and regulatory reporting.
Next up, there is a facility in place for pre-processing with institutional intelligence. Here, the underlying technology dynamically conditions agent behavior with custom SOPs, compliance documents, and user defined prompts.
Another detail worth a mention is rooted in the availability of an agent post processing layer. This one should really go the distance to facilitate hallucination detection, confidence scoring, and wrap around agents for compliance, security, fraud, regulations, and QA.
Then, there is an enterprise grade insights engine coming into play. The stated engine should enable users to uncover emerging trends, customer friction points, and LLM behavior anomalies through deep analytics.
Hold on, we still have a couple of bits left to unpack, considering we haven’t yet touched upon the prospect of accessing an agent augmented workforce, which packs together  an AI powered Agent Console committed to supporting human agents with summaries, recommendations, and compliance context.
Rounding up highlights would be a facility revolving around LLM deployment flexibility. Hence, you can seamlessly choose between trusted open models or deploy KaiGPT, a domain tuned LLM that runs securely within the bank’s cloud or on premises environment.
As for the availability, KAIgentic is currently in early access with select banks and credit unions, where it is supporting customer interactions, employee workflows, and contact center experiences. A broader launch is tipped to be unveiled later this year across North America, Europe, and Asia.
“Our vision is that every customer with a bank account will have a personal agent guiding their financial journey,” said Joshua Schechter, Chief Product and Innovation Officer at Kasisto. “KAIgentic makes that vision real, giving institutions the ability to earn trust, deepen relationships, and help customers build long term financial stability.”
