Gen-AI-Today

GenAI TODAY NEWS

Free eNews Subscription

Skyflow's Agentic Layer: A Breakthrough in AI Security

By Greg Tavarez

AI has advanced from simpler apps that use a single LLM for deploying intelligent agents. Therefore, enterprises face new data privacy, security and governance challenges.

As Agentic AI (i.e. autonomous agents capable of reasoning, decision-making and action) becomes more prominent, businesses face an entirely new set of challenges that traditional security measures are ill-equipped to solve. Here are a few:

  • Access to sensitive data: AI agents often require access to highly sensitive data, such as transaction histories or medical records, to perform tasks effectively.
     
  • Complex interactions: Agents engage in many-to-many interactions, increasing the risk of data exposure and unauthorized access.
     
  • Data management: This involves handling data, memory and state while retrieving information from multiple sources complicates governance.
     
  • Security threats: i.e. heightened vulnerabilities, including data leaks, exfiltration and AI-specific risks, such as prompt injections.
     
  • Regulatory compliance: This involves navigating strict regulations, including GDPR, CCPA, PCI DSS, HIPAA and emerging frameworks like the EU AI Act.

Without proper security, privacy and governance controls, these challenges can lead to breaches, regulatory penalties, and erosion of customer trust.

Enter Skyflow, the security and privacy company for the modern AI data stack.

Skyflow recently revealed new capabilities for Agentic AI to allow enterprises to build and deploy AI agents with a security and privacy trust layer with features that include protecting sensitive data flowing in and out of AI agents, auditing and logging, governance, and compliance with global and regional data protection measures.

Skyflow is designed to protect AI agents throughout their entire lifecycle. This includes safeguarding data collection, model training and agent execution.

During data collection, Skyflow identifies and anonymizes sensitive information in real-time to minimize risks and ensure compliance with global regulations. This prevents sensitive data from being used to train AI models, thereby protecting user privacy.

When training and fine-tuning AI models, Skyflow employs privacy-preserving techniques to secure training datasets. This ensures that sensitive information remains protected and does not inadvertently leak into the AI models powering the agents.

To safeguard agent interactions, Skyflow secures data flows across various tools and integrations, such as RAG, datastores and SaaS applications. This is to make sure sensitive data remains private during agent execution. Additionally, Skyflow's AI Gateway protects sensitive interactions with fine-grained access controls and real-time privacy enforcement.

By leveraging de-identification techniques and a purpose-built AI Gateway, Skyflow effectively protects sensitive information. The solution includes authorization and auditing tools to ensure compliance with regulations like GDPR, HIPAA, and the EU AI Act. This enables businesses to confidently build and deploy AI agents while adhering to legal requirements.

“Agentic AI will be built on a modern AI data stack,” said Anshu Sharma, co-founder and CEO of Skyflow. “If we want agents to act on behalf of our employees, customers, or enterprises, we will need to be able to trust them – and you can only trust a system if it’s built thoughtfully with guardrails for security, privacy and responsible use.”

With this announcement comes a new ecosystem for agentic apps. Skyflow also announced partnerships with Databricks (the data and AI company) and enterprise orchestration platform Workato, adding to its existing partnerships, Snowflake, AWS and others.

Be part of the discussion about the latest trends and developments in the Generative AI space at Generative AI Expo, taking place February 11-13, 2025, in Fort Lauderdale, Florida. Generative AI Expo covers the evolution of GenAI and will feature conversations focused on the potential for GenAI across industries and how the technology is already being used to create new opportunities for businesses to improve operations, enhance customer experiences, and create new growth opportunities.




Edited by Alex Passett
Get stories like this delivered straight to your inbox. [Free eNews Subscription]

GenAIToday Editor

SHARE THIS ARTICLE
Related Articles

The 4 Best Identity Verification Platforms for Deepfake Detection in 2026

By: Contributing Writer    5/8/2026

Deepfake technology has made it possible to generate convincing identities at scale, turning digital onboarding flows into a primary target for AI-dri…

Read More

Top 4 Agencies Optimizing Brands for Generative AI Search in 2026

By: Contributing Writer    5/8/2026

Generative AI search has shifted how information is discovered and evaluated. Platforms like ChatGPT, Perplexity, Google AI Overviews and Claude do no…

Read More

Can AI Outperform Humans, or Is Real Feedback Still King?

By: Contributing Writer    4/24/2026

Can AI really outperform human judgment, or does real user feedback still matter more? This article explores how AI reshapes online trust, review syst…

Read More

3 Mistakes Tech Companies Need To Avoid When Rolling Out AI Features

By: Contributing Writer    4/15/2026

These days, it seems like every tech company wants to have something related to AI in its products. It's not hard to understand why. If all your compe…

Read More

Inside the AI System Behind Modern Sports Fandom

By: Contributing Writer    4/1/2026

Sports consumption no longer begins and ends with a live match. A Champions League fixture, an NBA playoff game, or a Formula 1 race now plays out acr…

Read More

-->