RAD Security, a startup founded in 2021, pulled in $14 million in Series A funding to expand capabilities in its cloud and AI workload security platform and scale marketing, sales, and partnership efforts to extend its reach.
MSSPs are included in those partnerships, with co-founder and CEO Brooke Motta telling MSSP Alert that service providers can bring the platform to their clients.
“We provide MSSPs with the tools they need to efficiently monitor and protect both traditional and AI-driven systems,” Motta said. “By integrating RAD Security’s platform into their offerings, MSSPs can enhance their service capabilities, offer more comprehensive protection, and reduce the burden on their clients’ internal teams.”
MSSPs and other channel partners are a “cornerstone of RAD Security’s strategy,” she added. “Their ability to distribute our technology and provide value-added services helps us scale our solution to meet the diverse needs of businesses across industries. We invest heavily in building strong relationships with MSSPs and channel partners.”
Broad Protections for AI, Cloud
RAD Security’s platform uses AI to cast a wide protective blanket around enterprise and SMB hybrid cloud environments and AI workloads, collecting and analyzing data from myriad sources and querying security tools. It builds off RAD’s cloud detection and response (CDR) solution, RAD plans to continue expanding its reach.
The platform provides security for AI and large language models (LLMs), including monitoring them and detecting such AI-related threats as shadow AI, data exfiltration, prompt injection attacks, and compliance issues, according to the company. The insights collected by the platform also help reduce the mean-time-to-resolution (MTTR).
The CDR tools create a baseline of behavior across organizations’ hybrid cloud environments, making it easier to detect anomalous behavior like data exfiltration, down, and opportunities to rightsize an environment. The technology uses runtime security fingerprinting techniques for such tasks as analyzing identities, unauthorized access, and insider threats.
Turning Attention to AI Security
The opportunity to expand the platform’s capabilities comes at a time when enterprises are settling down after the initial rush to adopt generative AI – similar to the enthusiastic push to send to workloads into the cloud a decade ago – and beginning to think more about security for AI workloads, Motta said.
“Today, organizations are much more mindful of the need for security as cloud adoption has matured, and the security landscape is evolving rapidly,” she said. “With the explosion of AI, security risks have only grown more complex. … We're seeing a significant increase in AI-driven attacks and threats targeting cloud environments.”
CISOs are asking RAD a lot of questions about such issues as protecting sensitive data, security cloud environments, and ensuring AI models are resilient against attacks. They’re also seeking ways to manage the growing attack surface fueled by the rise of such technologies a AI and the cloud and to prevent unauthorized access as more critical workloads make their way to the cloud.
“One of the biggest questions we get from CISOs is around how to manage the security of increasingly complex environments – which now include AI workloads – with limited resources,” said the CEO, who helped found RAD after executive and security positions with such vendors as Sonatype, Wallarm, Bugcrowd, and Rapid7. “CISOs also ask how we help with regulatory compliance. The other concern we hear often pertains to AI model integrity: How do you secure the data feeding into AI models and ensure that AI-driven decisions are not compromised?”
RAD’s platform is designed to answer those worries in an automated fashion, she said.
A Competitive Field
The San Francisco-based company competes with both legacy cybersecurity firms – noting that vendors like Palo Alto Networks and CrowdStrike are building out the AI capabilities in their portfolios – AI security-focused startups, and specialized companies tackling adversarial machine learning or AI security models.
RAD’s differentiator “is our comprehensive, cloud-native platform that integrates security monitoring, AI-enhanced threat detection, and incident response in a single solution,” Motta said. “We focus on scalability, automation, and providing actionable insights that allow security teams to proactively defend their organizations without the need for overwhelming manual oversight.”
The platform can “seamlessly secure both cloud and AI environments,” she added, pointing to “our unique threat intelligence network that ensures rapid response to emerging AI-based attacks.”
The Series A funding was led by Cheyenne Ventures and included new investors Forgepoint Capital, Lytical Ventures, and Akamai and existing investors .406 Ventures, Vertex Ventures, and Gula Tech Adventures.”
