Private Network Check Readiness - TeckNexus Solutions

Confidencial.io to Preview Unified AI Data Governance Platform at RSAC 2025

Confidencial.io will unveil its unified AI data governance platform at RSAC 2025. Designed to secure unstructured data in AI workflows, the system applies object-level Zero Trust encryption and seamless compliance with NIST/ISO frameworks. It protects AI pipelines and agentic systems from sensitive data leakage while supporting safe, large-scale innovation.
Confidencial.io to Preview Unified AI Data Governance Platform at RSAC 2025
Image Credit: Confidencial.io

Confidencial.io, a data protection and compliance leader born from DARPA-funded research at SRI, is set to debut its AI data governance solution at this year’s RSAC, engineered to prevent data leaks and fuel secure, compliant innovation. Purpose-built for enterprise-scale AI, Confidencial serves as a governance layer seamlessly embedded within AI frameworks, covering AI workflows, Agentic AI systems, training workflows, and operations to ensure only authorized data flows through.


AI thrives on unstructured data—documents, transcripts, slides, and images—but without the right safeguards, an organization’s most valuable assets remain wide open.

RSAC findings reveal the urgency: 61% of CISOs cite IP leakage as their top concern, with customer data exposure close behind at 59%.

In response, AI and GRC leaders are deploying siloed protection and governance tools, each with its own access controls, resulting in a fractured patchwork where unstructured data slips through the cracks, exposed, vulnerable, and at risk.

“We’re addressing the unsustainable model of fragmented systems that can’t talk to each other,” said Karim Eldefrawy, Co-Founder and CTO at Confidencial.  “One of the biggest barriers to deploying AI in the enterprise is ensuring consistent data protection, governance, and control across the entire AI pipeline, regardless of where or how that information is accessed.”

Confidencial unifies governance and privacy controls by embedding a resilient, cryptographic layer directly into AI pipelines and document stores, ensuring seamless protection. It automatically identifies and secures sensitive unstructured data, preserving context while enabling AI to still extract valuable insights. By applying data-centric Zero Trust at the object level, Confidencial secures only the most critical data, reducing computing costs and streamlining compliance with NIST and ISO AI and Cybersecurity Frameworks.

“Unstructured data is the fuel powering modern AI, and adoption is picking up serious momentum, especially with the rise of tools like Microsoft Markitdown and IBM Docling that convert files into text for LLMs and text analysis pipelines,” said Eldefrawy. “Confidencial is the only solution that can find and cryptographically protect sensitive information within these converted files, at a granular level, before they enter AI workflows and systems. This provably ensures enterprise-grade cryptographic security and compliance while enabling organizations to safely and cost-effectively unlock more of their data for AI training and innovation.”

Fresh off the launch of the Cloud Protector, their next-gen DSPM solution for cyber defense, Confidencial now delivers a unified approach that secures sensitive data across both traditional and AI-driven environments. Visit Booth 5787 at RSAC to see firsthand how AI data governance meets cyber resilience.

About Confidencial
Our mission is to be woven into the technology fabric used by enterprises to govern and secure the sensitive information sitting inside their unstructured data. As an indispensable pillar of agentic AI infrastructure, Confidencial empowers responsible AI innovation and exploration without sacrificing ready and robust compliance, especially in highly regulated industries. No matter the threat or tactic, your data stays secure while getting more usable and valuable than ever. For more information, visit confidencial.io.

 


Recent Content

Looking to learn AI in 2025 without breaking the bank? This blog breaks down the best free AI courses and certifications from top platforms like Google, IBM, and Harvard. Whether you’re a beginner, teacher, or tech professional, you’ll find career-relevant learning paths, direct course links, and tips to get certified and start building AI projects today.
Explore the transformative potential of Open Radio Access Networks (O-RAN) as it integrates AI, enhances security, and fosters interoperability to reshape mobile network infrastructure. In this article, we explore the advancements and challenges of O-RAN, revealing how it sets the stage for future mobile communications with smarter, more secure, and highly adaptable network solutions. Dive into the strategic implications for the telecommunications industry and learn why O-RAN is critical for the next generation of digital connectivity.
Nvidia’s Open Power AI Consortium is pioneering the integration of AI in energy management, collaborating with industry giants to enhance grid efficiency and sustainability. This initiative not only caters to the rising demands of data centers but also promotes the use of renewable energy, illustrating a significant shift towards environmentally sustainable practices. Discover how this synergy between technology and energy sectors is setting new benchmarks in innovative and sustainable energy solutions.
SK Telecom’s AI assistant, adot, now features Google’s Gemini 2.0 Flash, unlocking real-time Google search, source verification, and support for 12 large language models. The integration boosts user trust, expands adoption from 3.2M to 8M users, and sets a new standard in AI transparency and multi-model flexibility for digital assistants in the telecom sector.
SoftBank has launched the Large Telecom Model (LTM), a domain-specific, AI-powered foundation model built to automate telecom network operations. From base station optimization to RAN performance enhancement, LTM enables real-time decision-making across large-scale mobile networks. Developed with NVIDIA and trained on SoftBank’s operational data, the model supports rapid configuration, predictive insights, and integration with SoftBank’s AITRAS orchestration platform. LTM marks a major step in SoftBank’s AI-first strategy to build autonomous, scalable, and intelligent telecom infrastructure.
Telecom providers have spent over $300 billion since 2018 on 5G, fiber, and cloud-based infrastructure—but returns are shrinking. The missing link? Network observability. Without real-time visibility, telecoms can’t optimize performance, preempt outages, or respond to security threats effectively. This article explores why observability must become a core priority for both operators and regulators, especially as networks grow more dynamic, virtualized, and AI-driven.

Currently, no free downloads are available for related categories. Search similar content to download:

  • Reset

It seems we can't find what you're looking for.

Download Magazine

With Subscription

Subscribe To Our Newsletter

Private Network Awards 2025 - TeckNexus
Scroll to Top

Private Network Awards

Recognizing excellence in 5G, LTE, CBRS, and connected industries. Nominate your project and gain industry-wide recognition.
Early Bird Deadline: Sept 5, 2025 | Final Deadline: Sept 30, 2025