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Home»Cybersecurity»iterate.ai secures $6.4 million to bring secure and scalable AI to the edge of the enterprise
Cybersecurity

iterate.ai secures $6.4 million to bring secure and scalable AI to the edge of the enterprise

versatileaiBy versatileaiJune 12, 2025No Comments4 Mins Read
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With a strategic push to solidify leadership in enterprise-ready artificial intelligence, Iterate.AI has raised $6.4 million in funding. The round is led by Auxier Asset Management and includes notable investors Peter Cobb, Mike Edwards and Dave Zentmyer. The former board member of EBAGS is a $165 million online travel retailer co-founded by repeatedly CEO Jon Nordmark.

This famous reunion is no coincidence. The founding team behind Iterate has long demonstrated its eerie ability to predict digital trends before reaching peaks. In 2015, they added “.ai” to their name. Seven years ago ChatGpt pushed AI into the mainstream. That same foresight now generates Iterate’s privacy-first, locally deployable AI assistants, and the interactions, its patented, low-coded AI development platform. Together, they shape how companies adopt and scale their unprecedented overall intelligent software without vendor lock-in.

A practical vision for the future of enterprise AI

“Iterate.AI’s approach to AI innovation is not only advanced, but also practical,” said investor Peter Cobb, who previously co-founded EBAGS and served on the Designer Brand Board (DSW). “The team is focused on solving real-world problems, including how to run powerful AI completely offline on edge devices and how to reduce deployment costs in the millions to just thousands.”

This philosophy is at the heart of Generate. A local first AI platform designed to run high-level power generation (RAG) workflows searched for on devices such as AIPCs and sales terminals. Unlike typical cloud-based solutions, Generate performs inference, document search, and automation locally for all language models. Enhance both privacy and performance. The internet-free architecture makes it ideal for sectors such as retail, healthcare, and government where data sensitivity and incubation period are important.

Agent AI infrastructure

Iterate’s flagship platform, Interactions, are generated by providing a visual drag-and-drop development environment for building AI workflows known as agent systems. These are not static chatbots. An autonomous agent that follows the logic tree, performs context-aware tasks, and integrates actions across internal documents, APIs, and enterprise databases.

The agent AI workflow built into Interplay relies on a variety of machine learning models that allow for subtle language understanding from lightweight small language models (SLM) optimized for embedded hardware to subtle large language models (LLM). The interaction also integrates vector database layers for semantic search and RAG pipelines, ensuring fast and accurate access to unstructured information such as contracts and financial filings.

Behind this innovation is Iterate co-founder and CTO Brian Sathiaathan, a former Apple engineer and an elite team that developed the first iPhone, one of the former members of the Secret Products group. His experience in hardware software optimization is clear about how interactions adapt to a variety of chipsets, from Intel CPUs and AMD GPUs to Nvidia Cuda Cores and Qualcomm Edge processors.

Buildings and Scaling Heritage

Mike Edwards, an investor who led EBAGS as CEO after Nordmark and former Staples executive, highlighted the trust and track record that the founding team shares. “This is a deep and experienced group that understands products, enterprise markets, and emerging technologies. The ability to combine visionary platforms with measurable ROIs for customers such as Ulta Beauty, Fujifilm, and Circle K is rare in today’s AI landscape.”

Previously, Zentmyer at Lands’ End praised the team for their hard work in securing critical hardware and distribution partnerships. “Iterate has spent the last 18 months gaining trust with giants like Nvidia, Qualcomm and TD Synnex. These relationships are hard to win and are examining the preparation of fake companies.”

Built for scales designed for security

Security and data sovereignty have emerged as a make-up or break-off factor in AI adoption. Air gap deployment, role-based access control, and an on-platform inference engine allow Iterate to have full control over where and how data is processed. That’s why many customers choose to generate and interact to run AI across secure government facilities, financial institutions and privacy-oriented retailers.

Also, unlike traditional AI stacks that require custom tweaks or extensive GPU provisioning, Iterate’s platform relies on modular components and zero trust architectures for rapid deployment with or without cloud access.

Conclusion

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