Confident Security Raises $4.2M to Bring Privacy-First AI to the Enterprise

Privacy Becomes the New Competitive Edge in Enterprise AI

A San Francisco company is tackling what many consider the most significant barrier to enterprise AI adoption. Confident Security launched this week with $4.2 million in seed funding and a bold promise: to make AI interactions provably private for businesses that handle sensitive data.

Confident Security's team brings impressive credentials to this challenge. CEO Jonathan Mortensen is a two-time founder who previously sold companies to BlueVoyant and Databricks. The broader team includes veterans from Google, Apple, Databricks, RedHat, and HashiCorp, with PhDs from Stanford, Cambridge, and Johns Hopkins. This combination of enterprise software experience and deep technical expertise in secure systems positions the company well for the complex enterprise sales cycles ahead.

The startup's emergence comes at a critical moment when enterprises across healthcare, finance, government, and legal sectors are wrestling with a fundamental tension. They need AI's competitive advantages but cannot afford to compromise data privacy. Traditional AI providers offer limited legal promises rather than technical guarantees, leaving regulated industries in a precarious position.

Jonathan Mortensen sees this tension as defining the next era of enterprise innovation.

“AI has become a baseline requirement across industries, but it’s introduced serious privacy concerns. This tension is especially pronounced in sectors like healthcare, finance, legal, and government—anywhere sensitive data or intellectual property is at stake,” he said. “The challenge is clear: how can organizations harness the power of AI while still retaining full control over their data? Those that figure out how to embed privacy into their AI strategies will be the ones to lead in this next phase of technological evolution.”

In a video interview posted yesterday by TBPN on X, Mortensen expanded on the kinds of data privacy risks that Confident Security aims to solve. He pointed to real-world examples of how enterprise secrets can unintentionally end up in public AI models. Watch the clip below for his full remarks.

Building on Apple's Foundation with Enterprise Focus

Confident Security's solution, called CONFSEC, represents an enterprise-grade implementation of Apple's Private Cloud Compute (PCC) architecture. The technology goes beyond typical encryption by using a combination of OHTTP, blind signatures, remote attestation, Trusted Execution Environments (TEEs), Trusted Platform Modules (TPMs), and transparency logs to create what the company calls "provably private" AI interactions.

The system works by first anonymizing data through encryption and routing it through services like Cloudflare or Fastly, ensuring servers never see the original source or content. Advanced encryption then allows decryption only under strict conditions, with publicly logged software that experts can review to verify its guarantees. This approach means that prompts and metadata cannot be stored, seen, or used for AI training, even by the model provider or any third party.

Unlike consumer-focused privacy solutions, CONFSEC is designed for enterprise deployment across any cloud or bare-metal environment. The technology has been thoroughly tested, externally audited, and is production-ready, positioning it as a foundational infrastructure component rather than an add-on security measure.

Unlocking Trillion-Dollar Markets Through Trust

The market opportunity for private AI infrastructure is enormous. In healthcare alone, a $4.7 trillion global industry, privacy concerns have stalled AI adoption. Similar constraints exist across financial services, government, and legal sectors, where regulatory obligations make traditional AI deployments risky. Confident Security aims to be the enabler that bridges this gap, helping enterprises and AI providers unlock these high-stakes markets.

“Confident Security is ahead of the curve in recognizing that the future of AI depends on trust built into the infrastructure itself. Without solutions like this, many enterprises simply can't move forward with AI,” said Jess Leão, Partner at Decibel, one of the company’s investors.

The business model offers three deployment options to meet varied enterprise needs:

1. Fully-managed cloud services with unlimited liability and indemnification for data breaches
2. Hybrid deployments combining cloud management with customer-controlled GPU nodes
3. On-premise installations for full control within private infrastructure

This flexibility gives organizations the ability to adopt AI while preserving their security posture and compliance requirements.

Backed by $4.2 million in seed funding from Decibel, South Park Commons, Ex Ante, and Swyx, Confident Security now has the runway to scale its technology and grow enterprise partnerships. Early discussions with banks, browsers, and search engines indicate strong demand for integrating CONFSEC into core infrastructure.

As AI becomes a competitive necessity, privacy infrastructure like CONFSEC may soon be as critical as firewalls and encryption. For organizations that have held back due to data sensitivity concerns, Confident Security offers a way forward that doesn't require compromising on either innovation or control. The question now is whether enterprises will act fast enough to seize the advantage.

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