Kasisto, a leader in AI for the banking sector, has announced the launch of KAIops, an operational intelligence layer integrated into its KAIgentic platform, designed to reduce incident costs, accelerate resolution times, and bolster customer trust for financial institutions.
KAIops leverages agentic AI to monitor system health, correlate telemetry data, generate root cause analysis (RCA) narratives, and execute approved responses. This approach aims to transition banking operations from a reactive investigative model to a proactive prevention-focused framework, enabling teams to move efficiently from identifying issues to resolving and preventing them. The system is engineered to help banks reduce outages and move toward self-healing operations.
Lance Berks, CEO of Kasisto, highlighted the significant financial and customer impact of critical outages in major banks. “Every major bank spends weeks on root cause analysis after a P1 outage, time lost, customers impacted, and hundreds of millions of dollars spent annually trying to understand what went wrong,” Berks stated. “KAIops changes that. Built on our KAIgentic platform, it shifts operations from reactive to predictive, from investigation to prevention. This is the future of banking operations: reduced incidents, eliminate guesswork, and achieve measurable cost savings at scale.”
Joshua Schechter, Chief Product and Innovation Officer at Kasisto, elaborated on the architectural advancements. “KAIops represents the next evolution of our agentic architecture, a system where AI agents collaborate, learn, and act independently across operational environments,” said Schechter. “By combining preprocessing intelligence, autonomous orchestration, and post-processing validation, KAIops creates a self-healing operational fabric for banking systems. It is the foundation for a future where every process is intelligent, auditable, and adaptive.”
KAIops operates through a three-phase model, currently available. In Phase 1, agents ingest various data points including logs, metrics, traces, tickets, and changes to streamline acknowledgement and resolution times, concurrently drafting RCAs for review. Phase 2 involves agents executing approved runbooks and remediations, such as restarting services, clearing cache, scaling resources, and rolling back components, all with role-based approvals and comprehensive audit trails. In Phase 3, the system’s agents evaluate planned changes, model dependencies, forecast potential risks, and recommend mitigations to prevent incidents before they impact customers. Across all operational phases, robust controls are implemented, including read-only access where appropriate, step approvals, reversible actions, and integration with existing change governance frameworks. These features are designed to result in lower incident costs, faster RCA completion, reduced escalations, and fewer minutes of customer impact.
Kasisto, recognized for its agentic AI platforms specifically developed for the banking industry, offers intelligent, compliant, and auditable AI experiences. Its platform orchestrates autonomous AI agents to operate securely within established banking regulatory and operational frameworks. At the core of Kasisto’s technology is KaiGPT, a proprietary large language model tailored for banking, which ensures domain-specific accuracy, reliability, and flexible deployment options. KAIops is now available globally to banks and credit unions.
