Kasisto

What is Kasisto?

Kasisto is a conversational AI platform for banks, and its product is called KAI. The platform lets a bank's customers ask about their money in plain language: current balance, recent transactions, spending questions, and account details. KAI reads the request, pulls from the bank's core systems, and answers in a conversation across whatever channel the customer chose.

Kasisto makes KAI. The company works with financial institutions and has built its platform around the language and rules of banking. That specialization is the point of difference: KAI arrives with financial domain training, so it recognizes banking intents and vocabulary without a bank teaching it the basics from scratch.

The audience is retail and commercial banks, credit unions, and other financial institutions that want a digital assistant inside their app and other channels. These buyers need answers tied to live account data and a vendor that understands the compliance and security demands of a regulated industry.

Key features

KAI centers on a set of capabilities aimed at conversational banking:

• ▸Core banking integration: KAI connects to the bank's core systems so it can answer questions about live account balances, transactions, and details rather than static content.
• ▸Transaction queries: customers can ask about recent activity, search past transactions, and get spending answers in conversation instead of scrolling through a statement.
• ▸Financial domain training: the platform ships with an understanding of banking terms, products, and intents, which cuts the work of teaching it the vocabulary of finance.
• ▸Multi-channel coverage: one conversational layer answers across the mobile app, web, voice, and messaging, so customers meet the same assistant wherever they bank.
• ▸Account and balance answers: KAI handles the common self-service questions that fill call queues, from balance checks to due dates and account status.
• ▸Compliance and security controls: the platform is built for a regulated industry, with the security posture and controls banks need before they put AI in front of customers.

The core integration matters most for value. Because KAI reads live account data, it moves past scripted answers and into questions only the bank's own systems can resolve. That is what separates conversational banking from a generic FAQ bot: the assistant speaks to the customer's own money, not general help text.

How well does it work?

KAI performs well on the account and transaction questions that make up a large share of banking support. Because it comes trained on the financial domain and connects to core systems, it handles balance checks, transaction lookups, and account queries with answers drawn from live data. For a bank, that deflects routine calls and gives customers self-service in the channels they already use.

The limits track the deployment model. KAI is a platform that a bank integrates into its systems, so results depend on the quality of that core connection and the scope of intents the bank configures. Complex or account-specific cases outside the configured scope route to a human, and getting the most from the platform takes planning around channels, data, and compliance sign-off. This is an enterprise deployment, not a switch you flip in an afternoon.

A practical way to raise KAI's coverage is to review the questions it cannot resolve, then expand the configured intents and data connections for the patterns you see most in the call queue.

Kasisto pricing

Kasisto uses custom pricing. There is no public rate card. Cost is quoted per institution and depends on the channels you cover, the deployment model, the depth of core integration, and expected volume. Buyers work through a sales and scoping process rather than a self-serve signup.

Because the price is negotiated, the useful comparison is what drives it. Here is how the pieces tend to shape a quote:

The model favors institutions that can commit to an integration project and value a banking-specific platform over a general chatbot. Smaller teams that want a published price and a quick setup will find the custom, sales-led approach a heavier lift, so scope the project and expected volume before you engage.

Who should use Kasisto?

Kasisto fits financial institutions that want a conversational assistant tied to their core systems. It suits these groups:

• ▸Retail banks and credit unions that want to deflect account and transaction calls with self-service in the mobile app and web.
• ▸Financial institutions that need answers grounded in live account data, not static FAQ content.
• ▸Banks in regulated markets that require a vendor built for the compliance and security demands of finance.
• ▸Digital banking teams rolling out voice or messaging assistants across several channels from one platform.

Kasisto is a weaker match for teams outside financial services, or for small businesses that want a low-cost, self-serve chatbot. The platform's depth in banking is its strength, and that same focus makes it wrong for general customer service use cases in other industries.

Alternatives and how it compares

Kasisto competes with both banking-specific assistants and general conversational AI platforms. The right comparison depends on how much you value financial domain depth against breadth.

• ▸Interactions and other banking IVA vendors: focus on financial-services virtual assistants, and suit banks weighing a specialist against Kasisto.
• ▸IBM watsonx Assistant: a general enterprise conversational AI that banks can configure for finance, with broad tooling but less banking training out of the box.
• ▸Kore.ai: an enterprise conversational platform with financial-services templates, aimed at institutions that want a configurable framework across industries.

Kasisto's edge is its narrow focus: a platform trained on the financial domain and built for core banking integration from day one. General platforms give you more breadth and often a published path to start, but a bank has to teach them the domain. If banking is the whole job, the specialist saves that work, so weigh domain depth against flexibility and price.

Limitations and getting started

Be clear about the trade-offs before you commit. Kasisto's price is custom, so there is no public rate and the buying process runs through sales. Deployment involves integrating with core banking systems, which takes planning and compliance sign-off, so this is an enterprise project rather than a same-day setup. The banking focus also means it is the wrong tool for use cases outside financial services.

Getting started follows a clear path:

1. 1Scope the channels and use cases you want to cover, from balance and transaction questions to account servicing.
2. 2Plan the core banking integration so KAI can read live account data through your systems.
3. 3Work through compliance and security review with the vendor before customer-facing launch.
4. 4Roll out on one channel first, watch the answers, then widen coverage and expand configured intents.

A staged rollout keeps risk low: start in the mobile app or web, confirm the account answers hold up against your core data, then extend to voice and messaging as the results earn trust. Treat the early phase as an integration and tuning period, since the platform's value grows with the depth of its connection to your systems.