Most AI Fails Because of This #AIstrategy #Shorts
AI isn't analytics. It's automation. Anirban Nandi explains why starting with business value is the key to scaling AI.
Security | Threat Detection | Cyberattacks | DevSecOps | Compliance
The Latest Cybersecurity News & Insights From Around The World
How to Scale AI with Unified Data #EnterpriseAI #Shorts
Want enterprise-wide AI adoption? Start with a unified data foundation. Anirban Nandi of Rakuten India breaks it down in 60 seconds.
Why RBAC Doesn't Work with AI Agents [And How to Fix It]
Role-Based Access Control (RBAC) is a fundamental, critical part of security architecture that prevents data from falling into the wrong hands. In regular data-based environments (deployed on the cloud or on-premise), RBAC is an effective measure in preventing unauthorized access, with a few exceptions, like successful hacking attempts or breaches. However, this system breaks down once AI comes into the picture. Let’s understand why – and what you can do about it.
Why Hosting LLMs On-Prem Doesn't Eliminate AI Risks [And What to do About It]
As AI steadily percolated into a growing number of use cases, adopting it has been a rollercoaster of confusion, chaos, and conundrums. One of the key concerns around AI adoption are the added risks. Issues like sensitive data leakage, AI hallucinations, inability to implement access control, and data breaches lurk the the cloud where LLMs are deployed.
3 CalypsoAI Alternates Analysed: Pricing, Key Capabilities, USP, Pros, & Cons
Over the past few years, enterprises have rapidly integrated GenAI into an increasing number of workflows and use cases. Amidst the rush and excitement to adopt a free tool that significantly boosts productivity, business leaders de-prioritized privacy, till it became a compliance issue. As privacy tools offering a quick patch quickly flooded the market, businesses ran into a new problem – which is the best tool?
Meet the Founders of Protecto: Securing Data for Agentic AI
In this video, we introduce the visionary founders behind Protecto — a company on a mission to make AI safe and compliant for the enterprise era. Amar Kanagaraj, Founder & CEO A second-time entrepreneur, Amar previously led a startup to a successful exit. He began his career as a developer at Sun Microsystems, then went on to lead product management for Microsoft Search & AI. With an MBA from Carnegie Mellon and an MS in Computer Science from LSU, Amar brings a powerful blend of business and technical insight to Protecto.
What No One Tells You About Scaling Enterprise AI | Ep: 1 | AI On The Edge
Watch this exclusive LinkedIn Live conversation at the frontier of privacy, security, and GenAI. Learn how to successfully scale AI initiatives in your enterprise with proven strategies that prioritize business value over technology complexity, featuring insights from Rakuten India's VP of AI & Data. Guest: Anirban Nandi – Vice President AI & Data @ Rakuten India Host: Amar Kanagaraj – Founder & CEO @ Protecto.
DeepSight by Protecto: AI-Native Sensitive Data Detection for Developers
Thanks to a wide range of use cases that automate manual activities, enterprises are rushing to integrate GenAI into their IT stack, only to realize they’ve hit a privacy wall. A concerning number of use cases involve the use of sensitive data like PII and PHI, risking data privacy and compliance. Enterprises today are becoming increasingly aware of these multifaceted risks associated with unfiltered AI usage and turning to the common solution available in the market – AI privacy tools.
3 CalypsoAI Alternatives Analyzed: Pricing, Key Capabilities, USP, Pros, & Cons
Over the past few years, enterprises have rapidly integrated GenAI into an increasing number of workflows and use cases. Amidst the rush and excitement to adopt a free tool that significantly boosts productivity, business leaders de-prioritized privacy, till it became a compliance issue. As privacy tools offering a quick patch quickly flooded the market, businesses ran into a new problem – which is the best tool?
How Businesses Using GPT 4.1 Can Comply With DPDP's Data Residency Bill
Until 2023, India’s data privacy landscape was largely unregulated – businesses didn’t have to worry about how they process and store data. Sensitive customer data like Personally Identifiable Information (PII) could travel around the world in 80 days and land back to its source without violating a single regulation. While the unregulated digital space was a boon for data dependent businesses, it was a bane for customer privacy.