The era of generative AI has accelerated everything for most of the companies we talk to, including development cycles (thanks to "ambiance coding" And "agentic swarming").
But even as they seek to harness the power of new AI-assisted programming tools and coding agents like Claude Code to generate code, businesses face a looming concern – no, not security (although that’s another one!): cloud spending.
According to Gartnerpublic cloud spending will increase by 21.3% in 2026 and yet, according to Latest Flexera Cloud Status Reportup to 32% of enterprise cloud spending is actually just wasted resources: duplicate code, non-functional code, outdated code, unnecessary scaffolding, inefficient processes, and more.
Today, a new company, Adaptive6 has come out of stealth to reduce this cloud waste in real time and automatically. The company, which announced total funding of $44 million, including a $28 million Series A led by US Venture Partners (USVP), aims to treat cloud waste not as a financial gap, but as a code vulnerability that must be detected and fixed.
Co-founded by CEO Aviv RevachAn experienced founder, former head of strategy at Taboola and former security research team leader for Israeli military intelligence unit 8200, the idea behind the company came directly from his experience working in the cybersecurity field.
“We realized it wasn’t a financial problem; it was an engineering problem," Revach told VentureBeat in an exclusive video call interview conducted recently. "We relied on our experience in cybersecurity, where finding vulnerabilities, scanning the cloud, identifying issues, linking them to the appropriate code, finding the developer or engineer responsible and fixing them – or, in some cases, going left and preventing them altogether… it was obvious that this is exactly what we need to do.
Adaptive6’s platform introduces a step change in how businesses manage infrastructure: instead of asking finance teams to spot inefficiencies they can’t fix, it allows engineers to resolve waste directly in their workflow.
By applying the rigor of cybersecurity (analysis, tracing and correction), Adaptive6 automates the cleaning of "Shadow Waste" in complex multi-cloud environments.
The transition: from billing to engineering
For years, the industry standard for cloud cost management has been "visibility"— dashboards that inform you of the latest news from the day before. Revach argues that visibility without action is just noise.
"The first generation of tools sort of tries to help with the financial side of the cloud," Revach told VentureBeat. "They typically cover the financial aspects of cloud cost: they show you costs going up, down, forecasting, and budgeting. But what they don’t really focus on is one of the biggest problems, which is waste."
According to Revach, the divide lies in ownership.
"Just as the cybersecurity CISO is trying to get everyone to think about security, now there’s the FinOps manager trying to get everyone to think about the cost of the cloud."
Technology: hunting "shadow waste"
The heart of Adaptive6’s offering is its "Cloud governance and cost optimization" (CCGO). It doesn’t just look for inactive servers; it looks for what the company calls Shadow Waste: hidden inefficiencies in application architecture and workloads that traditional cost management tools often overlook.
The system operates without agents, using standard cloud APIs to gain read-only access to environments.
Revach told VentureBeat that the platform analyzes AWS, GCP, and Azure, as well as PaaS layers like Databricks and Snowflake, and even deep into Kubernetes clusters.
"We have unique technology that allows us to essentially match every resource in the cloud. [where] we found an issue in the relevant line of code that actually created this issue," Revach explained.
This "From cloud to code" The technology allows the system to identify the specific engineer who made the change and provide them with a fix directly in their workflow (Jira, Slack, or ServiceNow).
Beyond basic resource sizing, the platform analyzes complex configurations, including those of emerging AI workloads.
Revach highlighted a specific technical nuance regarding "provisioned debit" for Large Language Models (LLM) on AWS.
He noted that engineers often struggle to balance commitment levels: committing too little performance risk, while committing too much wasted capital. Adaptive6’s engine analyzes these specific usage patterns to recommend the precise debit commitment needed, a level of granularity that general financial tools lack.
Revach also provided a specific example of "Shadow Waste" involving inefficiencies at the application level:
"If you’re using Python… and you’re not using the latest version, version 3.12 brought a major change that made it much more efficient," he said. "Most people, when they think about cloud cost, they don’t necessarily think about the Python version, so they just think about the size of the machine. By upgrading to this version, you gain efficiency so your code runs faster and you reduce costs."
The AI paradox: both problem and solution
While Adaptive6 uses AI to generate remediation scripts and "Fixes in 1 click," Revach was careful to distinguish his deep-tech approach from generic AI coding agents. In fact, he pointed out that AI-generated code is often wasteful itself.
"The code produced by AI is often not very effective because it was trained on a lot of code written by other people that didn’t necessarily take cost optimization and cloud governance into account." Revach warned.
That’s why Adaptive6 relies on a research team of experts rather than simple generative models to identify inefficiencies. "Just like with vulnerability research, you see cyber companies bringing in top security researchers to find things… we do the exact same thing for cost inefficiency," Revach said.
Impact and adoption
The platform is already used by major companies including Ticketmaster, Bayer and Norstella, with customers reporting a 15-35% reduction in their total cloud spend.
For global organizations, the ability to decentralize cost management is essential. "As complex as it may seem in a large organization, this is exactly our strong point," Revach noted. He cited a spectacular example of the tool’s effectiveness: "We had a case where a misconfiguration resolved by an organization actually saved over a million dollars."
Looking to the future
The system also includes "shift to the left" prevention capabilities, integrating directly into CI/CD pipelines. This allows the platform to scan code for cost inefficiencies before it goes live, effectively blocking costly architectural errors before they are deployed, much like a security scanner blocks vulnerable code.
"We detect what’s already wasting money, prevent new inefficiencies before they’re deployed, and fix them at scale." Revach said. By shifting responsibility to developers, Adaptive6 suggests that the future of cloud cost management won’t be in a spreadsheet, but in a pull request.
