Yuki, a data cost optimization startup, emerged from stealth with a $6 million seed round led by Hyperwise Ventures with participation from Yakir Daniel, founder of VelocitX, Tal Ventures, Fresh.fund, and Spot.io (Flexera).
Most organizations today support growing data and AI workloads by increasing their spending on the same rigorous infrastructure. This one-size-fits-all model forces teams with different SLAs, budgets, and performance needs into the same computing resources, creating significant inefficiencies as data volumes grow.
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Yuki team
(Photo: Aviv Shiloh)
“After building Spot, it was easy to see the problem Yuki was solving. Just as AI is turning data spend into a board-level problem, they are building a control plane for data cost optimization,” says Yakir Daniel, co-founder of Spot.io (acquired by NetApp and now part of Flexera), who participated in Yuki’s seed round and gave the team a vote of confidence.
At the core of the product is Yuki Fabric, an optimized AI model that serves as a unified control and automation layer across an organization’s data infrastructure, including native support for Snowflake, Google’s BigQuery, and Iceberg-based data lakes, positioning Yuki as the control layer for next-generation data architectures.
The model continuously learns workload behavior, SLAs, and cost/performance tradeoffs to optimize execution decisions in real-time. Yuki’s control layer sits above the vendor, eliminating duplication of infrastructure and processes, reducing compute and operational costs, and enabling SLA enforcement across teams, products, and workloads.
As enterprises increasingly adopt Iceberg to separate storage and compute, Yuki provides the missing intelligence layer to control how workloads consume those resources.
“Data is the only resource in an organization that no one truly controls. We know how to store it, but we don’t know how to manage it. We have the budget, we have the cloud infrastructure, we have the team, but the data itself has no control system,” says Ido Arieli Noga, CEO of Yuki. “For years, the default response to growth has been to put more money into the same one-size-fits-all infrastructure. That model is fundamentally broken and cannot scale in an AI-driven world. Yuki was built to be the control layer that knows and manages data infrastructure workloads in real-time. This becomes even more important in an era where teams are constantly running experiments, models, and new workloads, and many organizations are finding themselves paying huge sums for data and compute resources that no one is using anymore simply because no one took the time to manage or clean it up.
According to Noga, when data infrastructure becomes workload-aware and managed by an intelligent control layer, cost savings become a natural rather than manual outcome. As of 2025, customers using Yuki’s platform will save an average of approximately 42.6% on data costs, and for large enterprises, those savings can reach millions of dollars.
Aki is implemented through a simple and quick deployment process with no code or query changes required. Yuki’s AI platform manages workloads and priorities in real-time, clearly separating business-critical tasks from lower-priority internal processes. Based on the current state of the system, Yuki routes each query to the most efficient computing resources available at that time, reducing data costs in an environment where data volumes and compute consumption continue to grow, primarily due to increased AI adoption.
Yuuki’s business model is based on customer success, and we charge a percentage of the actual savings generated. If savings aren’t generated, customers won’t pay.
The cloud management tools market is estimated at approximately $9.8 billion and includes over 200 participating vendors. Growth is expected to continue as data volumes proliferate and organizations move toward unified data platforms. Enterprises must deal with fluctuating workloads, high query volumes, and dynamic computing costs, increasing the need for intelligent automation and real-time optimization.
Yuuki’s customers include cybersecurity companies such as Tenable and data-intensive media companies such as Angel Studios. The platform is chosen by organizations with large-scale data and AI operations that want to reduce costs, streamline operations, and maintain greater control over their data infrastructure.
Yuki was founded in 2025 by Ido Arieli Noga (CEO) and Amir Peres (CTO). The two have known each other since childhood and previously worked together in a joint venture, laying the foundation for a partnership. After 10 years of separate professional paths, a chance encounter led to us both working in the data field. They decided to join forces, but soon encountered a challenge common to many organizations: the inability to efficiently use data resources amid fluctuating workloads and constant high volume queries. Their research revealed that there was no true control plane for managing the data itself, which led them to build Yuki.
Yuki employs 15 people, most of whom are based in Israel, and also has team members in the US and UK. The funding will be used to accelerate growth in the United States by expanding our research and development center in Israel, deepening our product capabilities, supporting additional data platforms, and expanding our sales organization.
Yuki is a real-time optimization platform for Snowflake, BigQuery, and Iceberg-based data lakes that automatically improves cost and performance by optimizing execution based on system behavior. Yuki is metadata-only by design and is built for enterprise-grade governance, security, and predictable cost management.
