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Chaos Labs Announces $55M Series A Funding

Chaos Labs announced a $55 million Series A funding round led by Haun Ventures.

This significant investment, aimed at scaling onchain economic security, attracted prominent new investors including F-Prime Capital, Slow Ventures, Spartan Capital, and more. They join an impressive roster of existing backers such as Lightspeed Venture Partners, Galaxy Ventures, Wintermute Ventures, PayPal Ventures, General Catalyst, Bessemer Venture Partners, and Coinbase Ventures. The round also saw participation from strategic angel investors, including Kevin Weil (OpenAI CPO), Michael Shaulov (Fireblocks CEO), Anatoly Yakovenko (Solana CEO), Francesco Agosti (Phantom CTO), and Anton Katz (Talos CEO).

Chaos Labs plans to leverage this funding to accelerate new product development and scale its cutting-edge risk management platform. The platform currently features enhanced observability tooling, innovative risk oracles, and real-time parameter recommendations.

This Series A investment is the first led by Diogo Mónica, General Partner at Haun Ventures. Mónica shared his enthusiasm for the investment: "Chaos Labs has emerged as an industry leader; their rapid growth, despite volatile markets, speaks volumes about their product-market fit, brand strength, and product quality. As onchain finance matures to compete with its centralized counterparts, the need for world-class risk management tools, designed from the ground up for the blockchain stack, is both clear and intuitive."

Mónica added, "Meeting Omer and witnessing his intense focus and vision strengthened our conviction on Chaos Labs. We're excited to partner with Chaos Labs as they continue to safeguard and grow the industry."

Omer Goldberg, Founder and CEO at Chaos Labs, said: "Chaos Labs is building new products which merge previously siloed offchain market data, observability, and alerting with dynamic risk parameter adjustments. This new technology will build upon our existing stack and enable instant updates which reflect current market conditions."

Decentralized finance applications currently depend on manual risk management and isolated analysis of data feed performance to ensure platform integrity in variable market conditions. By comparison, centralized exchanges, including the Chicago Options Exchange utilize risk engines built directly on top of market data feeds.

"We're catching up to our CeFi counterparts and this is where it's going," said Goldberg.

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AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

Chaos Labs Announces $55M Series A Funding

Chaos Labs announced a $55 million Series A funding round led by Haun Ventures.

This significant investment, aimed at scaling onchain economic security, attracted prominent new investors including F-Prime Capital, Slow Ventures, Spartan Capital, and more. They join an impressive roster of existing backers such as Lightspeed Venture Partners, Galaxy Ventures, Wintermute Ventures, PayPal Ventures, General Catalyst, Bessemer Venture Partners, and Coinbase Ventures. The round also saw participation from strategic angel investors, including Kevin Weil (OpenAI CPO), Michael Shaulov (Fireblocks CEO), Anatoly Yakovenko (Solana CEO), Francesco Agosti (Phantom CTO), and Anton Katz (Talos CEO).

Chaos Labs plans to leverage this funding to accelerate new product development and scale its cutting-edge risk management platform. The platform currently features enhanced observability tooling, innovative risk oracles, and real-time parameter recommendations.

This Series A investment is the first led by Diogo Mónica, General Partner at Haun Ventures. Mónica shared his enthusiasm for the investment: "Chaos Labs has emerged as an industry leader; their rapid growth, despite volatile markets, speaks volumes about their product-market fit, brand strength, and product quality. As onchain finance matures to compete with its centralized counterparts, the need for world-class risk management tools, designed from the ground up for the blockchain stack, is both clear and intuitive."

Mónica added, "Meeting Omer and witnessing his intense focus and vision strengthened our conviction on Chaos Labs. We're excited to partner with Chaos Labs as they continue to safeguard and grow the industry."

Omer Goldberg, Founder and CEO at Chaos Labs, said: "Chaos Labs is building new products which merge previously siloed offchain market data, observability, and alerting with dynamic risk parameter adjustments. This new technology will build upon our existing stack and enable instant updates which reflect current market conditions."

Decentralized finance applications currently depend on manual risk management and isolated analysis of data feed performance to ensure platform integrity in variable market conditions. By comparison, centralized exchanges, including the Chicago Options Exchange utilize risk engines built directly on top of market data feeds.

"We're catching up to our CeFi counterparts and this is where it's going," said Goldberg.

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.