XONAI Raises $3.5M to Reduce Data Infrastructure Operational Costs at Enterprise Scale

  • Fundraising News
  • 01.06.2023 05:00 pm

XONAI, a cloud optimization solution helping organizations reduce data infrastructure costs, announced today it has closed $3.5 million in Seed funding. 

London-based Kadmos Capital led the round with participation from investors Adara Ventures, Deep Science Ventures, Nauta Capital, Notion Capital, and notable angels Mehdi Ghissassi, Director of Product Management for Google DeepMind, Martin Gould, former Head of Product for Spotify’s Content Platform, among others.

As cloud costs continue to skyrocket, data-driven organizations are increasingly investing in solutions to reduce cloud infrastructure spend. However, the margins for cost reduction in existing solutions are tied to how much-overprovisioned cloud resources can be right-sized. This leaves no margin for further improvement as these are not designed to optimize what is allocating those resources to begin with - data pipelines with demanding resource requirements.

XONAI tackles the challenge of optimizing what fundamentally drives up costs. “Even assuming infrastructure is perfectly rightsized, that software can ultimately only run as fast as it was originally designed to do so,” said Leandro Vaz, Co-Founder of XONAI. “We’ve made it possible to run those pipelines faster and cheaper with transparent machine code optimization specialized for big data analytics.”

XONAI’s differentiation lies in its non-invasive approach that sits between the hardware and the execution layer of the software it integrates with, providing immediate acceleration to data pipelines without any migrations or code changes. “XONAI increments the threshold for infrastructure optimization by allowing software to better utilize hardware – not unlike swapping an internal car engine with a faster and greener one,” added Leandro.

The addressable market for XONAI’s current solution is massive, encompassing dedicated petabyte-scale clusters running on market-leading data processing software, such as Apache Spark. The solution achieves a baseline 3x ROI on activation, immediately freeing budgets to allow engineering teams to shift focus from infrastructure optimization to new value-adding endeavours.

“We embarked on a mission to support data-driven organizations whose business imperatives rely on operating data infrastructure as cost-efficiently as possible. XONAI reliably reduces costs for running large-scale data analytics and without disruptions to operations,“ said Leandro. “We are very honoured to welcome Kadmos Capital as a strategic partner on this mission and help us through the next stage of growth.”

“Over the last decade, we have seen companies create analytics insights across every aspect of their trading activity. Now we are seeing an increased focus on the cost of those data pipelines. XONAI has arrived at exactly the right time to address this problem, and done so with an extremely clever and low-disruption approach. We are pleased to back XONAI in the next phase of growth,” said Graham York, Partner at Kadmos Capital.

The new funding will help XONAI further develop solutions on top of the increased spending reduction margin it adds to data analytics workloads at scale. “It’s not just about making workloads run faster. We have observed significant results in reducing the pressure these workloads put on large clusters, both on memory and network utilization. This allows a far wider range of potentially cheaper hardware selection for the customer, which we want to automate as our next step.”

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