AIceberg, a leading innovator of AI Trust; safety, security, and compliance technology, has officially raised a sum of $10 million in seed financing.
According to certain reports, the stated funding, which was led by SYN Ventures and Sprout & Oak, should tread up a long distance to help the company make meaningful advancements in conceiving AI transparency and compliance for enterprise and public entities.
AIceberg also took this opportunity to launch its AI trust platform, designed to provide enterprise-grade security with real-time, automated validation of all AI application traffic, from speech and text to images and source code.
More on that would reveal how this particular solution arrives on the scene bearing a mechanism to leverage power generative and agentic AI, all for the purpose of working as an AI firewall and gateway that monitors user prompts and model/agent responses. This it does to gauge risk signals, as well as implement security and organizational policies at scale.
Such a setup, like you can guess, makes it possible for organizations to seamlessly fight against any impending risks. Furthermore, they can adapt swiftly to emerging threats with real-time responses, agentic action controls, and customized security policies.
In case that wasn’t enough, users can also bank upon AIceberg’s advanced threat detection to keep their security posture always up-to-date for the latest attack vectors.
“Organizations adopting generative and agentic AI face critical challenges in ensuring safety, security, and compliance,” said Alex Schlager, CEO of AIceberg. “Many are operating with a false sense of security because, while AI TRiSM solutions powered by LLMs seem convenient, using LLMs to safeguard LLMs introduces systemic risks and architectural limitations that undermine their effectiveness. We are closing the security gap with AIceberg. Purpose-built to detect risk signals support safe AI adoption, AIceberg works independently of AI applications, using the content of input and output to detect and eliminate risks and power safe, secure, compliant use of generative models.”
Talk about Alceberg’s AI trust platform on a slightly deeper level, we begin the availability of stringent guardrails for safety. This translates to how the solution ensures that only use case relevant AI interactions are permitted to prevent unsanctioned, unsuitable, or illegal content, while simultaneously preserving user privacy at all times. Furthermore, it can automatically redact personal and sensitive information.
Now, we touched upon the technology’s bid to keep your security posture up-to-date, but what we haven’t mentioned yet is how it can detect common AI cybersecurity attack vectors like prompt injection, prompt leaking, or jailbreaking, and at the same time, perform sophisticated security analysis for agentic workflows.
Then, there is the potential for compliance, transparency, and auditability. Powered by explainable, non-generative AI models, users can come expecting to gain maximum accuracy and auditability from beginning to end.
Another detail worth a mention here is rooted in the availability of enterprise observability across all AI interactions. The idea behind providing such a feature is to let customers better understand common prompts, objectives, and intentions to improve user experience and access valuable business intelligence from communication mining of prompt/response pairings.
“AIceberg has an exceptional leadership and research team with deep expertise in AI, cybersecurity, and enterprise risk management,” said MJ Ramachandran, Partner at Sprout & Oak. “We partnered with AIceberg from its earliest days, recognizing the urgent need for enterprises—especially in regulated industries—to adopt generative and agentic AI safely and transparently. Our decision to incubate and invest early was driven by AIceberg’s pioneering approach to AI security, compliance, and explainability. We’re excited to continue supporting their mission to make AI adoption both powerful and responsible.”
