New Privacy Proxy Shields Enterprise Data from AI Chatbot Exfiltration
Urgent: Enterprise AI Use Raises Data Leak Risks, New Solution Arrives
Every time an employee types a prompt into ChatGPT, Claude, or other LLM-powered services, sensitive data may be transmitted to external servers. In enterprise settings, these prompts often contain customer names, social security numbers, medical records, and internal business data that should never leave the corporate environment.

Today, Kiji introduced its Privacy Proxy™, a tool designed to intercept and sanitize data before it reaches AI services. The proxy automatically redacts personally identifiable information (PII) and other confidential content, ensuring only anonymized prompts are sent externally.
"The genie is out of the bottle with generative AI, but enterprises cannot afford to trade compliance for productivity," said Dr. Elena Vasquez, a cybersecurity researcher at the University of Cambridge. "Kiji's approach offers a practical guardrail without requiring companies to abandon the technology."
Background: The Growing Threat of Data Exfiltration via AI
Generative AI tools have become indispensable for tasks like drafting emails, summarizing documents, and generating code. However, their cloud-based nature means every query leaves the organization's network, often traveling to third-party servers where data privacy policies may be opaque.
Recent studies show that over 40% of businesses have inadvertently exposed sensitive information through AI prompts. Compliance frameworks like GDPR, HIPAA, and CCPA impose strict penalties for such leaks, making it a top boardroom concern.
"We've seen employees paste entire customer databases into chatbots without thinking," noted Marcus Chen, CISO at a Fortune 500 financial firm. "The risk is existential if that data surfaces in a training set."

What This Means: A New Standard for AI Governance
The Kiji Privacy Proxy addresses the fundamental tension between innovation and security. By deploying the proxy on-premises or in a private cloud, organizations can continue using AI services while preventing data exfiltration.
Unlike traditional data loss prevention (DLP) tools that only alert after the fact, Kiji's proxy operates in real-time to mask or block sensitive fields. It integrates with major LLM platforms via API and requires no changes to user workflows.
"This is a game-changer for regulated industries," said Dr. Vasquez. "It allows legal, medical, and financial teams to safely harness AI's power without rewriting their compliance policies."
The proxy also logs all sanitized prompts for audit purposes, providing a clear trail for regulators. Early adopters report a 90% reduction in data exposure incidents within weeks, according to Kiji.
For enterprises struggling with shadow AI use, this tool offers a centralized way to enforce data handling rules. "We can finally say 'yes' to AI without sleeping poorly at night," added Chen.
Kiji will begin rolling out the Privacy Proxy immediately, with pricing based on query volume. The company plans to add support for additional languages and compliance frameworks in the next quarter.
Related Articles
- How to Transition Away from Claude Code as a Pro User
- Harnessing AI Agents for Hyperscale Efficiency: Inside Meta's Capacity Program
- Google I/O 2026 Live: Gemini 3.5 Debuts, Omni Model Goes Live, and Android XR Glasses Unveiled
- Google Blurs Line Between Search and AI: New Personal Agents Arrive
- How to Use GitHub Spec-Kit for Spec-Driven Development with AI Coding Agents
- OpenAI Prevents ChatGPT Goblin Obsession Before GPT-5.5 Launch
- Inside Stockholm's AI-Run Café: A Real-World Experiment in Automation
- MIT's SEAL Framework Lets AI Models Rewrite Their Own Code, Marking Leap Toward Self-Improving Systems