PrismSek90%
of incidents auto-remediated without analyst touch
Prevention
Data Loss Prevention
Stop sensitive data before it leaves, with actions precise enough to leave work unblocked.
The problem
Legacy DLP fails in both directions: it blocks so clumsily that the business routes around it, and it alerts so noisily that real exfiltration hides in the queue. Prevention only works when detections are precise and responses are proportionate.
How it works
What it covers
Data types
PIIPHIPCISecrets & tokensSource codeFinancial recordsCustom types
Detection
- Real-time classification on every egress event
- Destination risk scoring (external, personal, competitor, unknown)
- Behavioral baselines per user and team
- Exact data matching against your crown-jewel datasets
Actions
- Inline redaction and masking of sensitive spans
- Block, warn, or require justification with one policy toggle
- Real-time user coaching in Slack and email
- Automated quarantine, unshare, and access expiry
- Audit-ready incident records with lineage attached
AI coverage
- Redacts sensitive spans from prompts before they reach AI tools
- Blocks secrets and source code from unsanctioned copilots
- Applies the same policies to AI destinations as to any other egress
Deployment
SaaS multi-tenantDedicated single-tenantPrivate-cloud data plane
Regulations
GDPRHIPAAPCI DSSIndia DPDPGLBASOX
<5 min
mean time to respond
1.8%
of coached users repeat the violation within 90 days
Common questions
Will this block legitimate work?
Policies default to coach-first for ambiguous cases and block only high-confidence, high-risk events. You choose the posture per policy, per team, per destination.
How fast is inline enforcement?
Classification runs at ~180ms p95. Users experience it as instantaneous; there is no proxying of unrelated traffic.
Can we start in monitor-only mode?
Yes, and most customers do. Run policies silently, review what would have fired, tune, then flip to enforce.
Solutions this powers
See Data Loss Prevention on your data.
Connect one environment in a guided session and review real findings with a security engineer.