Surgical Robotics
Overview
The organization is a surgical robotics company focused on advancing patient care through innovative technology. It develops and manufactures robotic systems that support minimally invasive surgery, combining robotics, imaging, and software to help clinicians deliver precise and consistent treatment. With a strong emphasis on partnering with healthcare providers, this commitment to innovation extends beyond the operating room and into how the organization approaches internal priorities such as protecting sensitive data, including the proprietary designs at the core of its business, as AI tools become part of daily work.
Challenges
Protect intellectual property (IP). Safeguard proprietary surgical robotics designs from loss or exposure, since that IP is central to the company's value.
Segment data before adopting AI. Make sure sensitive and proprietary data is properly walled off so employees can use AI tools without that data resurfacing to someone who should not have it.
Keep pace with rapidly evolving technology. Manage a constant stream of new SaaS applications and AI tools entering the environment without losing visibility into where data goes.
Understand data flow end to end. Gain clear insight into where critical data resides and how it moves across both cloud and endpoint systems, so exposure can be caught early.
Overview
A surgical robotics company operating in a highly sensitive, IP-driven environment needed continuous visibility into how proprietary data moved across cloud and endpoint systems. As AI tools entered the workplace alongside a steady stream of new SaaS applications, the security team needed a way to keep sensitive data properly segmented so it could adopt new tools without losing control of its most valuable information.
“What's important in data security, in conjunction with AI, is being able to make sure the data the AI is using is not then giving that data to someone else. Our company is more cautious than other companies because we're pretty sensitive about our data.”
Challenge and Impact
For a surgical robotics company operating in a highly sensitive and IP-driven environment, protecting data is fundamental to protecting the business itself. Intellectual property and proprietary information are central to the organization's value, making data security inseparable from overall company security.
"Data security is integral to basically all company security. You are protecting IP and protecting the company's value."
— IT Systems Engineering Team Manager, Surgical Robotics Company
As AI tools, both generative and agentic, moved into the organization, that responsibility took on a new dimension. It was no longer enough to know where data lived. The team also needed to control what happened to that data once an AI tool had access to it.
"We have to be able to adapt and make sure AI is used appropriately and the data AI tools have access to is appropriately segmented. Being able to do that is important because it allows us to use different AI tools as they come around, because proper data security is already in place."
— IT Systems Engineering Team Manager, Surgical Robotics Company
That responsibility is made more complex by the constant evolution of the technology environment. New SaaS applications, AI tools, and collaboration platforms are continually introduced, creating new paths for data to move and new challenges for maintaining control.
"There's always a new SaaS tool or other application, and people want to put data into them. If you don't have a good understanding of where your data is going, you can't protect it properly."
— IT Systems Engineering Team Manager, Surgical Robotics Company
As a result, the challenge extended beyond simply putting controls in place. The organization needed a clear understanding of where data lived, how it moved, and who had access to it across both cloud and endpoint environments, so it could manage AI adoption and everyday risk with equal confidence.
Solution
AI Adoption Built on a Foundation of Data Segmentation
Map where data lives and the associated access
Cyberhaven gives the team a live map of where data lives and who can reach it, the starting point for any decision about what a human or AI tool should or should not be allowed to touch.
"One of the most important things DSPM does is it allows you to have a map of where data is and who has access to it. If you can understand that, you have a much easier time creating those segmentations and just understanding your environment, because there's always a new SaaS tool or other application and people want to put data into them."
— IT Systems Engineering Team Manager, Surgical Robotics Company
Turn that map into action
Visibility only matters if it leads somewhere. By integrating with the tools the team already uses, Cyberhaven turns a map of data into a prioritized list of what to fix first.
"It's about understanding the action, not just the data itself. With Cyberhaven, I can go back and integrate it with Microsoft Exchange, Slack, SharePoint, and it will give me actionable information: your data is here, this is the type of data you have, here is who has access to it. Now I know what the most important things are and where to take action."
— IT Systems Engineering Team Manager, Surgical Robotics Company
Marry the cloud and the endpoint
Segmenting data for AI use only works if the team can see the whole path data takes, not just half of it. Cyberhaven brings cloud and endpoint visibility together in one view.
"You need to know what's happening in the cloud and what's happening on the endpoint. If you only know what's happening on the endpoint, then you have no idea how your data is being exfiltrated through the cloud, because you're just watching the endpoint. Marrying those two points in the environment is critical to correct DLP. For me, DSPM is almost under DLP, because you need to understand where your data is, who has access to it, and where it can move on the endpoint and in the cloud."
— IT Systems Engineering Team Manager, Surgical Robotics Company
See the full chain of custody with data lineage
When something does go wrong, or when the team needs to confirm an AI tool never touched data it shouldn't have, data lineage shows the complete path a file took, not just a snapshot.
"When you have data lineage, you can see the file was downloaded from here, made all these modifications, and then got exfiltrated there. You have the full chain of actions, and you can very quickly make a decision on what action to take. Data lineage is the key to that. Understanding the origin of your data is critical to understanding where it's going."
— IT Systems Engineering Team Manager, Surgical Robotics Company
A network map that earns trust fast
For the team, one moment made the platform's approach concrete rather than theoretical.
"The first ‘aha’ moment with DSPM was seeing the network map where it showed you the data type, where it was stored, and being able to match that to files on the endpoint. It's impressive to say this file hash is the exact same as the file hash there, and I can trace where it started on the endpoint and where it ended up in the cloud."
— IT Systems Engineering Team Manager, Surgical Robotics Company
Looking Ahead
As AI tools and data permissions continue to change, the team sees visibility as something that has to keep pace in real time, not on a delay.
"With DSPM, frequency of the scan is critical. If something is available for twenty-four hours, that's a huge amount of damage that could happen. Any DSPM platform that is on a twelve or twenty-four hour scale is almost useless. You need to be able to react appropriately and quickly to a potential data leak."
— IT Systems Engineering Team Manager, Surgical Robotics Company
Looking ahead, Cyberhaven's ability to show data flow, permissions, and access across cloud, endpoint, and AI tools alike remains central to how the organization plans to keep adopting new technology without losing control of its most sensitive information.
Conclusion
For the organization, protecting sensitive data, and safely adopting the AI tools built to use it, depends on a clear and continuous understanding of how that data moves across the environment. Cyberhaven has become a core part of enabling that visibility and giving the team confidence to bring on new tools as they arrive.
"I would describe Cyberhaven as a modern DLP solution. It's about understanding where data started, where it ended, and the actions taken in between."
— IT Systems Engineering Team Manager, Surgical Robotics Company
Beyond the technology itself, the ongoing partnership has also mattered to the team.
"My experience with Cyberhaven's customer service team has been excellent. The product brings in the customer, but the customer service keeps the customer there."
— IT Systems Engineering Team Manager, Surgical Robotics Company
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