Your security stack is only as strong as the data intelligence behind it.
Sensitive business data identified beyond traditional PII
Fewer false positives
vs. industry-standard DLP (40–60%)
Faster time to value than traditional implementations (months vs. weeks)
A simple intelligence layer that makes Purview, Defender, Sentinel, and Copilot enforce smarter decisions.
Step 1
Where unstructured data actually lives
Endpoints
File Servers
Cloud
Step 2
Business context + sensitivity + risk
Contextual classification
Risk signals
Sensitive data beyond PII
Embedded metadata
Step 3
Policies finally work as intended
Purview
Defender
Sentinel
Copilot
Kriptos injects business-aware data intelligence into Microsoft tools so
protection becomes accurate, automated, and fast to operationalize.
Each pillar adds the data intelligence Microsoft tools need to protect what matters — automatically
Labels finally reflect real business risk
— not just PII patterns.
Problem: Microsoft Information Protection
depends on accurate labeling, but generic
classifiers miss business-critical data.
Effective information protection policies
from day one — without manual tuning.
Same data, different risk — enforced automatically.
Problem: Generic DLP rules create noise,
false positives, and blind spots.
Dramatically fewer false positives and
stronger protection where it matters.
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AI access governed by data risk,
not default permissions.
Problem: Copilot can surface any data
users can access — including sensitive
content that shouldn't reach AI.
Deploy Copilot with confidence —
without exposing crown-jewel data.
Events become risk signals
when data context is added.
Problem: Sentinel sees activity, but lacks
context to assess real insider risk.
Faster investigations and higher-
confidence insider threat detection.
Labels finally reflect real business risk
— not just PII patterns.
Problem: Microsoft Information Protection
depends on accurate labeling, but generic
classifiers miss business-critical data.
Effective information protection policies
from day one — without manual tuning.
Same data, different risk — enforced automatically.
Problem: Generic DLP rules create noise,
false positives, and blind spots.
Dramatically fewer false positives and
stronger protection where it matters.
AI access governed by data risk,
not default permissions.
Problem: Copilot can surface any data
users can access — including sensitive
content that shouldn't reach AI.
Deploy Copilot with confidence —
without exposing crown-jewel data.
Events become risk signals
when data context is added.
Problem: Sentinel sees activity, but lacks
context to assess real insider risk.
Faster investigations and higher-
confidence insider threat detection.
Kriptos does not replace Microsoft security tools — it activates
them with business-aware data intelligence.
Purview is powerful for enforcement — Kriptos adds the missing intelligence to make
it accurate, fast, and complete across unstructured data.
| Capability | Purview Alone |
|
|---|---|---|
| Visibility across endpoints & file servers | Limited | Full coverage (endpoints, servers, cloud) |
| Business-context classification (beyond PII) | Limited | High accuracy, business-aware |
| Non-PII sensitive data (IP, strategy, financial models) | Partial | Full coverage |
| Labeling at scale | Manual + tuning-heavy | Automated labeling at scale |
| DLP precision (false positives) | Higher noise | Context-driven precision |
| Time to Operational Impact | 12-24 months of tuning | 3-5 weeks to operational labeling |
| Audit-ready compliance evidence | Basic | Prioritized exposure + defensible evidence |
| Insider risk context for Sentinel/SOC | Event-driven | Data + behavior risk context enrichment |
