AetherData.
Find, classify and protect sensitive data — one model.
Data security that starts where the data is: discovery, ML classification, posture (DSPM), access governance and DLP enforcement, with ransomware and insider-threat detection. Ten terabytes a day of discovery, classification over 95% accurate, inline enforcement under 200ms, ransomware caught in under 30 seconds — data-security parity, self-hosted and air-gapped.
- Engines
- 12, one platform
- Discovery
- ≥ 10 TB/day
- Classification
- ≥ 95%
- Deploy
- Cloud · self-hosted · air-gapped
Discover, classify, protect.
Data security is fractured — a discovery tool, a classifier, a DSPM dashboard, an access governance product and three DLP agents — and the data slips through the gaps between them. AetherData runs the whole problem on one model, so the sensitive record, who can reach it and the attempt to exfiltrate it are one story under one identity.
Multi-repository discovery
Find sensitive data wherever it lives — cloud, on-prem, SaaS, endpoints, databases and file shares — at over 10 TB per day per scanner, across petabytes and billions of objects.
ML classification
Classify by content and context, not just regex — PII, PHI, PCI, source code, secrets — at ≥95% precision and ≥90% recall, so the labels are trustworthy enough to enforce on.
Data security posture (DSPM)
Map where sensitive data lives, who can reach it and how it's exposed — the data-centric posture the perimeter tools can't see.
Access governance
Analyse billions of ACLs to find over-permissioned access, stale entitlements and toxic combinations — and drive least-privilege across the estate.
Activity monitoring
Watch who accessed what, at over 100,000 events per second — the audit trail and the behavioural baseline for every sensitive data store.
DLP enforcement
Block exfiltration inline across email, web and endpoint in under 200ms — content- and context-aware, so legitimate work isn't blocked and real leaks are.
Endpoint agent
Endpoint DLP under 3% CPU — control USB, cloud upload, copy/paste and print of sensitive data without slowing the device.
Ransomware & insider threat
Detect ransomware from its behaviour on the data — mass encryption, abnormal access — in under 30 seconds from onset, and surface the insider exfiltrating quietly.
Adaptive policy
Risk-adaptive enforcement that tightens when risk rises — a user, a device or a destination that's suddenly anomalous gets stricter controls automatically.
Incident management
Investigate and respond to data incidents with the full lineage — what was touched, by whom, from where — assembled into a case, not a pile of alerts.
Compliance
GDPR, CCPA, HIPAA and PCI mapping with continuous evidence and DSAR support — the regulator's questions answered from the same telemetry.
Data security copilot
Ask where your sensitive data is, who can reach it, and what to fix — in plain language, grounded in your discovered and classified estate.
Access, posture and DLP, on one model.
The incumbents each own a slice — access, classification or enforcement. AetherData covers the whole data-security problem, and runs where your data is allowed to live.
Accurate enough to enforce on.
DLP gets disabled when it's noisy or slow. These are the budgets the platform is built to.
per scanner
precision / recall
email · web
no device drag
events per second
permissions analysis
from onset
data never leaves
One platform for the data.
Discovery, classification, DSPM, access governance and DLP collapse into one model, one queue and one audit trail.
Good to know.
Those split the problem: data access governance is strong on access governance and on-prem, data-governance suites on Microsoft-native classification, the DLP vendors on enforcement. AetherData runs discovery, ML classification, DSPM, access governance, activity monitoring and DLP enforcement on one model — so the sensitive file, the over-permissioned access to it and the exfiltration attempt are one story, with classification accurate enough (≥95%) to actually enforce on.
Endpoint DLP runs under 3% CPU, and inline email/web enforcement is under 200ms — content- and context-aware so it blocks the real leak without blocking legitimate work. Risk-adaptive policy tightens only when the risk genuinely rises.
Yes — from the behaviour on the data itself: mass encryption and abnormal access patterns are detected in under 30 seconds from onset, before the blast radius spreads, alongside the quiet insider exfiltrating over time.
No — it's self-hosted and fully air-gapped. Discovery and classification run where the data lives, scanning over 10 TB/day per scanner across petabytes, with nothing leaving the boundary.
Protect the data, wherever it lives.
Discovery to classification to access governance to DLP, on one model with one incident queue. Request access to deploy it self-hosted or air-gapped so the data never leaves.
Part of Aether Security — one platform across thirteen domains. Data security sits on the same foundation as the rest of Aether — one model, every discipline.