Ask Sophia: Data Security Posture Management
Discover shadow data, map risk to people, and remediate fast across cloud, SaaS, and On-Prem.
Ask Sophia: Data Security Posture Management
Discover shadow data, map risk to people, and remediate fast across cloud, SaaS, and On-Prem.
Transcript
Hi, I'm Sophia, Lightbeam's AI product guide.
I help security teams understand where sensitive data exists, who can
access it, and where it may be exposed.
In this short walkthrough, I'll show you how Lightbeam uses AI to discover
sensitive data, connect it to identities, and help reduce risk
across your environment. The real problem is that sensitive data spreads
faster than security teams can track, so exposure hides in cloud
stores, SaaS apps, on-premise systems, and even AI
assistants. Lightbeam fixes that by tying each sensitive record to the
person it belongs to and automating remediation through policy workflows
with audit-ready reporting. Let me pull up how sensitive data gets tied to
identities and remediated before exposure turns into a bigger problem.
What we're tackling here is the blind spot of sensitive data slipping across cloud,
SaaS, and on-premise environments, and the dashboard gives us a single view of
health, volume, and the most urgent policy alerts so we can start closing
gaps fast.
Going ahead, the SharePoint risk cover page surfaces exactly how
much PII and financial data sits in that collaboration hub,
tying the alerts to concrete file counts and linking to ongoing data subject
requests.
From here, we shift to an entity-centered view, looking at a person
rather than a file, which immediately makes classification actionable by
connecting every sensitive element back to the individual it represents.
Once you drill into that entity, the view aggregates all its attributes,
the system storing them, and any policy violations, giving you the
context needed to prioritize remediation based on real impact.
Moving on, the connected data sources panel highlights which repositories
hold the most sensitive assets, enabling the team to focus
remediation before AI tools like Copilot can ingest the data.
After that, the SharePoint repository view quantifies exposure,
44K Social Security numbers and 19K credit cards,
so we can target the highest risk buckets with precise actions.
Finally, the SharePoint lens provides a file overview report of
high-sensitivity file types, delivering audit-ready evidence and a
clear path to reduce risk across the environment.
I help security teams understand where sensitive data exists, who can
access it, and where it may be exposed.
In this short walkthrough, I'll show you how Lightbeam uses AI to discover
sensitive data, connect it to identities, and help reduce risk
across your environment. The real problem is that sensitive data spreads
faster than security teams can track, so exposure hides in cloud
stores, SaaS apps, on-premise systems, and even AI
assistants. Lightbeam fixes that by tying each sensitive record to the
person it belongs to and automating remediation through policy workflows
with audit-ready reporting. Let me pull up how sensitive data gets tied to
identities and remediated before exposure turns into a bigger problem.
What we're tackling here is the blind spot of sensitive data slipping across cloud,
SaaS, and on-premise environments, and the dashboard gives us a single view of
health, volume, and the most urgent policy alerts so we can start closing
gaps fast.
Going ahead, the SharePoint risk cover page surfaces exactly how
much PII and financial data sits in that collaboration hub,
tying the alerts to concrete file counts and linking to ongoing data subject
requests.
From here, we shift to an entity-centered view, looking at a person
rather than a file, which immediately makes classification actionable by
connecting every sensitive element back to the individual it represents.
Once you drill into that entity, the view aggregates all its attributes,
the system storing them, and any policy violations, giving you the
context needed to prioritize remediation based on real impact.
Moving on, the connected data sources panel highlights which repositories
hold the most sensitive assets, enabling the team to focus
remediation before AI tools like Copilot can ingest the data.
After that, the SharePoint repository view quantifies exposure,
44K Social Security numbers and 19K credit cards,
so we can target the highest risk buckets with precise actions.
Finally, the SharePoint lens provides a file overview report of
high-sensitivity file types, delivering audit-ready evidence and a
clear path to reduce risk across the environment.
