Adaptive Data Risk Management
The alert was the easy part
The alert was the easy part
Why Nootron
What does Nootron do for a data security program?
What does Nootron do for a data security program?
Nootron normalizes the signals your DLP, DSPM and DAG tools produce, resolves them against your policy and data ownership model, routes to whoever owns it for remediation and records as audit evidence.
Improve incident response
Empower analysts
to reduce risk
Decide in the moment,
not in committee
Drive value from
your existing tools
Survive the audit
One alert format.
One severity scale.
One queue.
Nootron normalizes alerts from Microsoft Purview, Zscaler, Proofpoint, and DSPM into a single signal schema with a single severity model. Duplicate signals about the same subject, the same asset, or the same actor are correlated into one case instead of four tickets. The analyst opens one queue in the morning and can get to meaningful work, not six consoles.
Features
Cross-vendor signal normalization into a common event schema
Correlation by actor, asset, data class, and time window
Deduplication across tools reporting the same underlying event
Unified severity model mapped back to each source tool’s native scale
Structured escalation chain: event, alert, incident, case
No rip and replace, no lost history, just the data security tool changing while your decisions stay
Healthcare
Financial Services
Your DAG flagged, your DSPM classified, your DLP triggered, and your SWG blocked, all on the same clinician. Then, it became four parallel investigations until Nootron aggregated it into one case with one owner and one resolution path.
Filter
3
ID
SEVERITY
STATUS
#ID-4472
High
New
#ID-4472
High
Open
#ID-4471
Critical
Resolved
#ID-4473
Low
Resolved
Steven Johnson
Improve incident response
Empower analysts
to reduce risk
Decide in the moment,
not in committee
Drive value from
your existing tools
Survive the audit
One alert format.
One severity scale.
One queue.
Nootron normalizes alerts from Microsoft Purview, Zscaler, Proofpoint, and DSPM into a single signal schema with a single severity model. Duplicate signals about the same subject, the same asset, or the same actor are correlated into one case instead of four tickets. The analyst opens one queue in the morning and can get to meaningful work, not six consoles.
Features
Cross-vendor signal normalization into a common event schema
Correlation by actor, asset, data class, and time window
Deduplication across tools reporting the same underlying event
Unified severity model mapped back to each source tool’s native scale
Structured escalation chain: event, alert, incident, case
No rip and replace, no lost history, just the data security tool changing while your decisions stay
Healthcare
Financial Services
Your DAG flagged, your DSPM classified, your DLP triggered, and your SWG blocked, all on the same clinician. Then, it became four parallel investigations until Nootron aggregated it into one case with one owner and one resolution path.
Filter
3
ID
SEVERITY
STATUS
#ID-4472
High
New
#ID-4472
High
Open
#ID-4471
Critical
Resolved
#ID-4473
Low
Resolved
Steven Johnson
Improve incident response
Empower analysts
to reduce risk
Decide in the moment,
not in committee
Drive value from
your existing tools
Survive the audit
One alert format.
One severity scale.
One queue.
Nootron normalizes alerts from Microsoft Purview, Zscaler, Proofpoint, and DSPM into a single signal schema with a single severity model. Duplicate signals about the same subject, the same asset, or the same actor are correlated into one case instead of four tickets. The analyst opens one queue in the morning and can get to meaningful work, not six consoles.
Features
Cross-vendor signal normalization into a common event schema
Correlation by actor, asset, data class, and time window
Deduplication across tools reporting the same underlying event
Unified severity model mapped back to each source tool’s native scale
Structured escalation chain: event, alert, incident, case
No rip and replace, no lost history, just the data security tool changing while your decisions stay
Healthcare
Financial Services
Your DAG flagged, your DSPM classified, your DLP triggered, and your SWG blocked, all on the same clinician. Then, it became four parallel investigations until Nootron aggregated it into one case with one owner and one resolution path.
Filter
3
ID
SEVERITY
STATUS
#ID-4472
High
New
#ID-4472
High
Open
#ID-4471
Critical
Resolved
#ID-4473
Low
Resolved
Steven Johnson
THE MAIN FEATURE
What does Nootron do that the data security industry keeps stepping around?
What does NOOTRON do that the data security industry keeps stepping around?
It answers the three questions that decide whether a data risk incident gets resolved, and it answers all three in the same place. Detection tools answer none of them. Ticketing systems answer none of them. These questions are the reason data risk incidents remain underserved.
Your Workspace
3
ID
SEVERITY
STATUS
#ID-4471
Critical
New
#ID-4472
High
New
#ID-4472
High
Open
Steven Johnson
Total incidents
2301
Needs Attention
316
How long does it take to trace a single incident back to its root cause today?
On average, 3 to 4 hours across multiple disconnected tools. With correlated signals, that drops to minutes.
How long does it take to trace a single incident back to its root cause today?
On average, 3 to 4 hours across multiple disconnected tools. With correlated signals, that drops to minutes.
How many analyst hours per week go to correlating signals across consoles, and what is that worth annually across the team?
Most teams burn 10+ hours a week cross-referencing consoles by hand — that's over 500 hours a year, or one full analyst doing nothing but copy-paste.
How many analyst hours per week go to correlating signals across consoles, and what is that worth annually across the team?
Most teams burn 10+ hours a week cross-referencing consoles by hand — that's over 500 hours a year, or one full analyst doing nothing but copy-paste.
What's the real cost of alert fatigue on your team?
When analysts spend less time sorting noise and reconstructing context, they can spend more time applying institutional judgment, accelerating decisions, and creating measurable impact in data risk operations.
What's the real cost of alert fatigue on your team?
When analysts spend less time sorting noise and reconstructing context, they can spend more time applying institutional judgment, accelerating decisions, and creating measurable impact in data risk operations.
Resources
Someone had to say it
Observations, bold claims and product thinking
Product
Data Security: Platform or Best-of-Breed Is the Wrong Fight
Are we there yet? A decade of consolidation promises says we should be. Simplify the stack. Reduce the vendor count. Cut the spend.
Read
Field notes
Data risk needs operating controls, not more policy
Policy tells us what should happen. Controls make it happen, become measurable, and provable. If unstructured data is the generally the main course for AI initiatives, we might be overdue for a controls library for data risk?
Read
Data risk decisioning, ADRM, Data governance, AI governance, Agentic AI
The Seven Strands of a Defensible Decision
Detection got fast. Deciding didn't. Here's what a data risk decision has to be made of to hold up in the AI era, one strand at a time.
Read
Resources
Someone had to say it
Observations, bold claims and product thinking
Product
Data Security: Platform or Best-of-Breed Is the Wrong Fight
Are we there yet? A decade of consolidation promises says we should be. Simplify the stack. Reduce the vendor count. Cut the spend.
Read
Field notes
Data risk needs operating controls, not more policy
Policy tells us what should happen. Controls make it happen, become measurable, and provable. If unstructured data is the generally the main course for AI initiatives, we might be overdue for a controls library for data risk?
Read
Data risk decisioning, ADRM, Data governance, AI governance, Agentic AI
The Seven Strands of a Defensible Decision
Detection got fast. Deciding didn't. Here's what a data risk decision has to be made of to hold up in the AI era, one strand at a time.
Read
Resources
Someone had to say it
Observations, bold claims and product thinking
Product
Data Security: Platform or Best-of-Breed Is the Wrong Fight
Are we there yet? A decade of consolidation promises says we should be. Simplify the stack. Reduce the vendor count. Cut the spend.
Read
Field notes
Data risk needs operating controls, not more policy
Policy tells us what should happen. Controls make it happen, become measurable, and provable. If unstructured data is the generally the main course for AI initiatives, we might be overdue for a controls library for data risk?
Read
Data risk decisioning, ADRM, Data governance, AI governance, Agentic AI
The Seven Strands of a Defensible Decision
Detection got fast. Deciding didn't. Here's what a data risk decision has to be made of to hold up in the AI era, one strand at a time.
Read
FAQ
Questions, answered
Have another question?
What is Nootron?
What is Adaptive Data Risk Management?
Does Nootron replace Microsoft Purview, my DLP, or my DSPM?
How is Nootron different from a SOAR platform?
How is Nootron different from Security Copilot for Microsoft Purview?
Is Nootron like Torq or Prophet AI?
Who is Nootron for?
How do I get access to Nootron?
Limited seats. Build the category with us.
NOOTRON is onboarding a small number of regulated enterprises as early adopters, live in your environment before general availability, with implementation support from Infolock and a say in what ships next.
Limited seats. Build the category with us.
NOOTRON is onboarding a small number of regulated enterprises as early adopters, live in your environment before general availability, with implementation support from Infolock and a say in what ships next.
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