For Bojan Belejkovski, Kyriba Liquidity Planning is not theoretical. He used it in a previous treasury role, saw the value firsthand, and is now bringing those lessons into his current implementation at Voltava, an automotive manufacturer and value-add assembler that grew significantly through the combination of Detroit Manufacturing Systems, Android Industries, and Avancez.

That prior experience gave Bojan a clear view of what Liquidity Planning could deliver: faster forecasting, less manual effort, better visibility, and a more scalable treasury model. As Voltava continues to grow, Bojan is building treasury around a connected data foundation with Kyriba at the center. As he explains, “as you keep growing and you want to build scalable treasury, you need a system to rely on and you need something to be at the core of your treasury processes.”

Proven value, applied to a new challenge

Before joining Voltava, Bojan had already experienced what Kyriba Liquidity Planning could do. In a previous treasury role, a monthly forecasting process that took roughly eight hours was reduced to about 30 minutes. That result shaped how he thinks about the technology and why he is implementing it again.

The bigger story is what that experience revealed. By shifting forecasting from spreadsheet-driven effort to a system-driven process, treasury can redirect time from assembling information to reviewing outputs, collaborating with stakeholders, and supporting the business.

Bojan describes Kyriba as a kind of treasury data foundation. Once bank statements, ERP data, payment files, historical information, and cash positioning are connected, Liquidity Planning can help turn that foundation into forward-looking planning. Or, as Bojan puts it, “if you think of it as your treasury data lake, then you’re just tapping right into it and getting value out of it.”

Building the right foundation for Liquidity Planning

At Voltava, Bojan is approaching the implementation strategically, drawing on what he learned before. His first priority is making sure the right data is flowing into Kyriba correctly: bank statements, ERP data, payments from ERPs to banks, and historical information that can support forecasting.

For customers evaluating Liquidity Planning, his advice is to start before the model is built. Treasury teams should understand where their data is, how it is structured, and how it needs to be mapped into Kyriba. That includes cash concentration, account structures, mapping values, budget codes, flow codes, and cash flow codes.

This preparation matters because Liquidity Planning is most effective when it reflects how treasury already thinks about the business. Rather than starting from a blank page, teams can translate the logic of an existing Excel forecasting model into Kyriba and make that logic repeatable. As Bojan explains, the process can begin with “rebuilding what you may have as a perfect Excel model.” From there, teams can “rebuild that logic into Kyriba,” so that “it really is a click of a button and data comes through.”

AI, visibility, and better forecasting

Once the right data foundation is in place, Liquidity Planning can become more than a structured forecasting workflow. For Bojan, the next layer of value comes from applying AI to connected treasury data. Its machine learning functionality uses historical cash flow patterns to generate forecast suggestions, helping teams spot likely future cash movements faster and reduce manual forecasting effort.

Bojan sees value in the way Liquidity Planning combines machine learning with emerging agentic AI capabilities. That combination matters because treasury teams are not only trying to create a forecast. They are trying to make forecasting information easier to access, easier to review, and easier to use in recurring planning cycles.

He describes the AI approach as a way to "replace many hours," particularly when paired with processes designed to scale. For Voltava, that means building a planning environment that works for today's needs while also creating a foundation for tomorrow's treasury operations.

One place to see everything

For Voltava, the broader value of Kyriba is centralized visibility. Bojan does not want his team spending time going through files, pulling data from different formats, or calling banks. His goal is simple: “I just want to go to one place and see everything.”

That visibility changes how treasury operates day to day. Bojan describes Kyriba as sitting at the center of the treasury ecosystem, connected to ERPs, banks, FX portals, payroll portals, APIs, reporting, dashboards, and future agentic capabilities. With that foundation, the team can spend less time chasing information and more time using it.

That confidence is central to Liquidity Planning. With connected data, AI-powered tools, and the ability to build forecasting logic directly in Kyriba, Voltava is creating a treasury process designed not only for today, but for what comes next.

As Bojan puts it, visibility is key. For Voltava, Kyriba Liquidity Planning provides that visibility while helping treasury reduce manual effort, streamline forecasting workflows, and build a scalable foundation for growth.