Meet Us at IAPP Privacy.Security.Risk 2024
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Join us in Los Angeles for an exciting edition of PSR this September 22-24
Our team will be waiting for you at Booth 212 in the Exhibit Hall- Privado.ai platform overview and meet our founding team. Sign up for a 15 minute run-through.
- Meet Nishant Bhajaria, author of “Data Privacy: a runbook for engineers". Sign up for a one-on-one chat.
- Play the highly addictive strike-a-light game and win amazing prizes!
- Pick a high quality and fashionable Privado bag.
Want to get live updates from us during the event? Follow us on LinkedIn
One-on-one with Nishant Bhajaria
Sign up for a one-on-one discussion with Nishant Bhajaria, author of the seminal publication on technical privacy “Data Privacy: a runbook for engineers”. Enjoy a unique opportunity to discuss directly with Nishant how a technical approach to privacy can help your organization achieve its privacy compliance objectives. Submit the form to reserve a time with Nishant.
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Request one-on-one
Privado bridges the privacy engineering gap by automating personal data visibility and privacy governance.
In 15 minutes our team can give you a run-through of Privado's core capabilities including:
- Dynamic Data Maps
- Digital Tracking Governance
- Smart Assessments
- Auto-Risk Discovery
- Developer Tool integrations
Request an overview
Tuesday September 24, 2pm to 3pm
Data is the aftermath. What you see in a data store is the result of collection points, processing and storing that is determined by logic. And this logic is ruled by your software products and the code it is built on. An efficient approach to data privacy should then start with the code Join Nishant Bhajaria and Vaibhav Antil for a discussion of how visibility and governance at the code level will give your programs a strong foundation regardless of scale.
What you will learn:
- Understand how software and code give you context for your data.
- Gain insights on how visibility and governance of code will enable true and scalable governance over data.
- Discover practical steps to implement code- level privacy measures effectively.


