Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI On The Edge: Scaling AI - Part 2.

Hosted by Amar Kanagaraj, CEO of Protecto, chats with Manoj Mohan — a veteran AI leader who has built large-scale data & AI platforms for Intuit, Meta, and Apple.

GenAI data security is now a critical concern for every enterprise. In this insightful episode of AI On The Edge, Dinesh Chandrasekhar, Founder and Chief Analyst at Stratola, sits down with Amar Kanagaraj (CEO, Protecto.ai) and Steve Shah (SVP Products, Automation Anywhere) to explore the future of data privacy, agentic automation, and securing LLMs in enterprise settings. Learn how two of the industry's top innovators are setting AI guardrails, preventing sensitive data leaks, and embedding privacy-by-design into large-scale automation.

Welcome to another episode of AI On The Edge, where we explore how AI is transforming manufacturing—and how you can stay ahead of the curve. In this exclusive conversation, Amar Kanagaraj (Founder & CEO of Protecto) sits down with Vicky Sareen, a Principal Leader at Forbes Marshall, to uncover.

What does it really mean to be AI-native? In this episode of AI On The Edge, host Amar Kanagaraj (Founder & CEO, Protecto) chats with Manoj Mohan — a veteran AI leader who has built large-scale data & AI platforms for Intuit, Meta, and Apple. Manoj shares practical insights on: Whether you’re a CTO, engineer, or AI enthusiast, you’ll walk away with actionable lessons on how to build and scale AI responsibly.

Most companies think their AI is secure — but the truth is far more complex. In this episode of AI On The Edge, Amar Kanagaraj (Founder & CEO, Protecto) and Sabrykrishnan Loganathan (Strategy Advisor, Peloton Interactive) break down what really goes into building secure, trustworthy AI systems for enterprise. You’ll learn: This is your masterclass on enterprise AI security. Don’t be in the 99% — watch and join the top 1%.

In this video, we take you under the hood of Protecto’s technology stack and show how it powers context-aware security for AI—while hiding the complexity behind simple APIs. At the core are two intelligence layers: You’ll also see how Protecto’s DeepSight engine, entropy-based tokenization, secure vault, and inference-level APIs deliver enterprise-scale security, compliance, and auditability. Protecto enables enterprises to safely unlock their data for GenAI, copilots, and Agentic workflows — without leaks, oversharing, or loss of AI capability.

Protecto replaces the patchwork of DLPs and DSPMs with AI-native controls, so you can safely unlock enterprise data for AI. Prompts, models, and context power Agentic AI. But context is also the most volatile and exposed layer - where 90% of enterprise AI risks originate. Intellectual property loss, unauthorized access, privacy violations, compliance failures - all start in the context. That’s why Protecto brings Zero Trust controls to data in AI.

Traditional role-based access control (RBAC) was built for structured systems - not for the messy, unstructured data that powers today’s AI workflows. In this video, we explore real-world healthcare scenarios where RBAC breaks down like mental health notes, lab results, and substance use histories buried in clinical documents. You’ll see how Protecto’s Context-Based Access Control (CBAC) solves this by understanding the user, prompt, and context - and enforcing policies in real time, without breaking AI functionality.

AI consumes massive volumes of unstructured data — emails, documents, reports, and prompts. Hidden within them are sensitive details: customer PII, salary data, intellectual property, and confidential financial information. Without the right safeguards, one innocent prompt can lead to costly data leaks, compliance violations, and privacy risks. Traditional security tools like RBAC, DLPs, and prompt filters weren’t designed for AI. They fail because AI doesn’t see folders — it consumes raw context. That’s where Protecto’s Context-Based Access Control (CBAC) comes in.