Five ways to eliminate
data visibility gaps
and reduce risk
Discover the essential steps for enabling no-gap data visibility in your enterprise including:
- How to find all your data
- Understanding your data
- Data movement and tracking
- How to identify the full entitlement chain
- How to map your data flows and usage
Sign up to receive the free ebook
What Our Customers Say About Us

Generative AI poses a unique data challenge because once data goes into a model, it’s challenging to control the output. Enterprises need assurances that GenAI models are compliant and secure, and that they will not divulge sensitive information. Bedrock’s ability to automatically learn what data is most material to the business and put boundaries between sensitive data and GenAI models is a game-changer. This capability reduces friction and enables us to safely and responsibly bring GenAI to customers faster.
Suha Can, CISO at Grammarly

I believe that effective security requires looking at the full lifecycle of how customer data is handled. This means getting accurate visibility, enabling data perimeters, and proactively reducing data risk. Bedrock’s innovation excites me and aligns with how I think about protecting data and managing risk effectively.
Mukund Sarma, Sr. Director Product Security, Fastest Growing US Fintech Co.

Being able to look at a certain user and follow along on a map to see what that user can access, how they can access it, and where they can access it from in Bedrock’s platform was phenomenal, especially as somebody who was sitting here trying to do it manually.
Andrew Kuhn, Product Security Engineer, House Rx