Noma Launches with $32M to Secure AI Lifecycle for Enterprises

Israeli AI security startup Noma launches with $32M to secure the 'Data and AI Lifecycle' - SiliconANGLE

Israeli AI security startup Noma launches with $32M to secure the 'Data and AI Lifecycle' Israeli artificial intelligence enterprise security startup Noma Security Inc. today launched and announced that it had raised $32 million in funding to enhance its end-to-end AI security platform, grow its customer base and increase its headcount. Founded in 2023, Noma offers end-to-end security solutions tailored to the "Data and AI Lifecycle," the process of developing, deploying and managing data-driven AI models, including data collection, model training, testing, deployment, monitoring and securing data pipelines and runtime environments. The company's flagship platform is built to protect every stage of the AI supply chain, from development to production, ensuring that data science and machine learning workflows remain secure. Noma argues that the rapid adoption of AI has thrown data science and machine learning teams in the spotlight and has introduced new security risks. Noma's platform counters these risks and assists teams through the provision of end-to-end AI discovery, security, protection and compliance. The company's platform focuses on critical areas of the AI lifecycle, including Jupyter notebook security, data pipeline protection and MLOps vulnerability management. Noma's tools scan for exposed secrets, code vulnerabilities and configuration issues, allowing the platform to prevent potentially disastrous breaches while enabling teams to build with confidence. Noma's offering includes AI Security Posture Management, a service that automatically inventories AI assets, builds a Bill of Materials for model components and ensures proper governance over training data. The approach addresses the risk of vulnerable or malicious open-source models, as well as the management of sensitive data, which is crucial as AI scales across industries. In production environments, Noma's AI Runtime Protection mitigates real-time threats such as adversarial prompt injection attacks, model jailbreaks and unauthorized data access. The runtime protection helps prevent incidents that traditional application security tools might miss to ensure that AI-driven applications operate safely within organizational policies and standards. Noma's Series A round was led by Ballistic Ventures and came on top of a previously undisclosed seed round led by Glilot Capital Partners Ltd., with participation from Cyber Club London Ltd. Other investors in Noma include current and former chief information security officers from McDonald's Corp., Google DeepMind Ltd., Twitter (X Corp.), Atlassian Corp., BNP Paribas S.A., T-Mobile US Inc. and Nielsen Holdings plc. "As security and compliance become more top of mind for organizations adopting AI, embedding security from the start ensures that innovation can flourish without compromise," Jake Seid, co-founder and general partner of Ballistic Ventures, commented on the round. "Noma's approach gives AppSec teams full visibility and confidence while empowering data science teams to move fast and drive business value."

Noma arrives to provide security from data storage to deployment for enterprise AI solutions

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More As 2024 nears its conclusion, the state of play in enterprise technology is that companies of all sizes and domains are keen to leverage their data in generative AI applications that improve internal (employee-facing) or external (cusomter/partner-facing) processes. However, ensuring that they do so securely is another challenge -- especially for companies that don't specialize in security. For many enterprises, their existing security solutions may also be inadequate or unprepared for the AI era and the many capabilities they want to unleash with their data piped through AI. Enter Noma, an Israeli startup specializing in AI enterprise security, that today exits stealth mode wih a Series A round led by $32 million Ballistic Ventures and supported by Glilot Capital Partners and Cyber Club London, as well as angels including the chief information security officers (CISOs) from companies like McDonald's, Google DeepMind, Twitter, Atlassian, BNP Paribas, T-Mobile, and Nielsen. Noma provides a comprehensive security platform that ensures integrity of enterprise customer's data from the very start, before they do anything to it, all the way through to leveraging it to train and/or deploy AI models and custom applications. The platform is already in use by several Fortune 500 companies. Tackling security challenges in the data and AI landscape Niv Braun, co-founder and CEO of Noma, told VentureBeat in an interview about the pressing need for targeted security in AI workflows. " "Today's AI and data science models face unique security risks, like prompt injection and data leakage, that simply aren't covered by standard security tools," he said. These issues are becoming more common as organizations experience security incidents due to misconfigured MLOps tools and unverified open-source models. This gap inspired Braun and his co-founder, Alon Tron, to create Noma. "My co-founder Alon and I served together in the military, and we both saw firsthand the gap in security tools for data science and AI workflows," Braun said. "In application security, we had tools that helped software engineers work securely, but for data teams -- data scientists, engineers, and analysts -- there was nothing similar. They were left unprotected." Both co-founders served in Israel's elite 8200 intelligence unit. Combining expertise from their backgrounds in security and data science, they quickly a team skilled in AI and application security. What Noma's three-tiered platform offers Noma's platform is designed to safeguard every stage of AI model development and operation, incorporating security tools that cover: Braun emphasized the consolidation that Noma's platform offers to customers. "Our platform includes three products: data and AI supply chain security, AI security posture management, and AI runtime defense." But, for those that wish, each of the three domains can be applied ad-hoc, a-la-carte. "A major strength of our platform is that it consolidates everything into one solution," Braun explained. "While customers can choose just one part, most prefer the comprehensive approach." Braun clarified that Noma offers a choice between an all-inclusive enterprise license and a modular, product-based option, both on an annual software-as-a-service (SaaS) subscription basis. He said 95% of customers have so far chosen the integrated, all-in-one approach. Braun's comments suggest that the enterprise license is positioned as the most cost-effective, flexible choice for customers looking for extensive, organization-wide access to Noma's solutions. Maximum flexibility and ease-of-use Noma's platform is compatible with diverse environments, supporting cloud-based, SaaS, or self-hosted configurations, and installs within minutes without requiring code changes. "Integration is easy," said Braun. "All customers need to do is connect our platform via API, and we automatically map and scan everything in their environment." This frictionless setup means data science teams can implement security controls without disrupting their workflows, a feature that Noma highlights as essential in high-velocity, AI-powered development. Kobi Samboursky, Founder and Managing Partner at Glilot Capital Partners, extolled the value of Noma's unified approach in a press release: "AppSec evolved over decades with fragmented tools for static and dynamic analysis, open source, supply chain, and runtime. Security teams have come to realize that they need consolidated solutions. Noma is uniquely positioned to tackle this problem from the start, consolidating multiple use cases into a single platform." In addition, Noma can be applied by those without extensive training in security or data infrastructure. "We engage with both data and AI teams as well as security teams, and our platform doesn't require deep expertise in either field," he said. "Even in cases where security teams ran POCs (proof of concepts) without data science teams involved, they found it easy to integrate and use."" At the same time, the platform turns these subjects into digestible, easy-to-understand insights for employees working in all departments. "The platform itself is very self-educating," Braun noted. "It explains the basic principles of security in a way that application security teams are familiar with, but with a new 'data and AI' layer." Addressing industry wants and needs As security and compliance become more critical in AI adoption, Noma aims to facilitate collaboration between data science and security teams. "Our mission is to bridge the gap between data science and security teams, making it easy for both to collaborate on securing AI workflows," Braun said. Noma's approach is designed to improve transparency and simplify security processes. "We make security simple for both teams, providing clear, understandable risk information and steps for remediation," he added. "It's all about reducing friction and improving collaboration." Jake Seid, Co-founder and General Partner at Ballistic Ventures, emphasizes the importance of security from the outset in a statement in a press release. "As security and compliance become more top of mind for organizations adopting AI, embedding security from the start ensures that innovation can flourish without compromise," Seid said. "Noma's approach gives AppSec teams full visibility and confidence while empowering data science teams to move fast and drive business value." Noma's ambitions are to lead the emerging field Noma's entry into the market marks a significant step in securing AI-driven business operations at scale. With the growing use of AI in critical applications, the potential for security vulnerabilities in AI workflows becomes more acute. Noma's platform provides a much-needed safeguard, allowing enterprises to harness AI's potential without compromising on security. In addition, Noma is actively contributing to AI security standards and has participated in the development of U.S. government guidelines, such as NIST SP 800-218A, through its involvement with the OWASP AI Exchange. With $32 million in fresh funding and early traction among high-profile customers, Noma seeks to become a leader in the emerging field of data and AI lifecycle security.

Noma is building tools to spot security issues with AI apps

Companies are concerned that their eagerness to adopt AI has made them more vulnerable to cyberthreats. Per a recent poll of over 350 IT leaders, more than half of the executives surveyed said the complexity of AI applications weakened their organization's cybersecurity posture. More than two-fifths of executives believe their security teams lack the skills needed to protect their AI applications and workloads, per another survey. The demand for solutions to secure AI apps has spawned an entire cohort of startups. HiddenLayer and Protect AI, for example, focus on defending AI systems from adversarial attacks, while Cranium provides visibility into AI systems at the application level. A new venture emerging from stealth today, Noma Security, does all of this and more, claims co-founder and CEO Niv Braun. The startup is developing tools to identify vulnerable data pipelines and code in data science environments, as well as threats like prompt injection attacks. Braun launched Noma with Alon Tron after leaving customer experience automation firm Verint, where he noticed a "significant blind spot" for security teams in the data and AI lifecycle. "Existing tools are designed for the traditional software lifecycle," Braun said. "However, the data and AI lifecycle is inherently different. It involves distinct R&D processes, relies on different technologies, and faces unique technical vulnerabilities within AI models." Noma is designed to help spot -- and fix -- misconfigurations in the components used to develop and run AI applications. For instance, the platform scans for "sensitive" data in model training datasets, such as text containing personally identifiable information. Braun argues that companies can be better equipped to deal with threats if they can consolidate AI app security functions in one dashboard that can be deployed in cloud-based and self-hosted environments. "Many single-function security solutions are flooding the market, trying to capitalize on the AI hype," he said. "By helping companies understand their AI application footprint and giving them governance controls, Noma is not only helping organizations minimize and mitigate risk, but also giving them the confidence they need to expand their AI usage faster and to more high-value parts of the business." Noma, founded in 2023, already has paying customers, Braun says, including Fortune 500 clients in B2B software, financial services and retail. The startup recently closed a $25 million Series A funding round that Braun said was preempted by investors; Noma had cash to spare. "We decided to accept the [$25 million], even with substantial funds still in the bank, to accelerate our development and especially our go-to-market teams and efforts," he said, adding that Noma plans to double the size of its 20-person team in the coming year. Ballistic Ventures led Noma's Series A, which brings the company's total capital raised to $32 million. Noma raised $7 million in a previously-undisclosed seed round led by Glilot Capital Partners with participation from Cyber Club London.