Context-Aware Vulnerability Management Platform
Built for the way
attacks actually happen.
The platform that reads context, not just CVEs. Deep OS-level telemetry combined with autonomous AI analysis to deliver zero-hallucination risk scoring and exact remediation steps.
Sub-millisecond telemetry without the agent bloat.
Artemes AI utilizes a lightweight telemetry layer to expose your operating system as a high-performance relational database. Real-time queries execute across Windows, Linux/Unix, and network devices with near-zero performance impact.
- No persistent agent overhead: Query-based collection means we only ask for what we need, when we need it.
- Comprehensive tables: Native access to processes, users, network_interfaces, listening_ports, kernel_modules, and file events.
"Unlike legacy agents that consume 15% CPU just sitting there, Artemes AI's collection layer is virtually invisible to our infrastructure."
uid = 0
port = 6379
protocol = 6
1. Raw Telemetry
Our distributed telemetry streams actual system state, running processes, and open ports to GCP Pub/Sub.
2. Autonomous AI Analysis
Gemini reads loaded modules and config files to determine if a vulnerable code path is truly exposed.
3. Zero-Hallucination Output
Findings are strictly anchored to the specific OS artifact. AI interprets but never invents.
Autonomous AI: Context-aware security analysis.
Legacy tools just match CVE IDs against installed package versions. Artemes AI's proprietary analysis layer, powered by enterprise-grade AI models, acts as an autonomous senior analyst.
It understands whether a vulnerable library is actually in the execution path. It compares live states against CIS Benchmark configurations in real-time.
Zero Hallucination Architecture
The "source of truth" is always the deterministic OS telemetry data. The AI engine is strictly constrained to interpret the exact configuration values and processes provided, preventing fabricated findings.
Risk Scoring: Beyond theoretical CVSS.
CVSS is a starting point, not the answer. A critical vulnerability on an isolated internal dev server is not the same risk as a medium vulnerability on a public-facing API gateway.
Artemes AI's proprietary scoring model factors in exploitability in YOUR specific environment, exposure surface, lateral movement potential, and blast radius.
The output? A ranked list of 10-15 actual, imminent threats—not 847 theoretical ones.
Heap buffer overflow in libwebp
Found on prod-edge-gateway-01
$ sudo systemctl restart nginx
Remediation-as-Code.
Not vague advice like "update OpenSSL". We provide the exact commands with environment context, ready to be executed or automated.
Immediate (Critical)
Shell-ready commands generated instantly via API for emergency patching.
GET /api/v1/findings/{id}/remediationInfrastructure Integration
Native integration with Ansible, Terraform, and Chef to fix drift at the source.
- name: Update libssl
apt:
name: libssl1.1
state: latestCompliance Auto-mapping
Every fix is automatically tagged to CIS controls, NIST CSF, and SOC 2 criteria.
Mapped: CIS 5.2, SOC 2 CC6.1
End-to-End Architecture
API-First Design
Built for technical buyers. Everything you can do in the UI is available via our REST API with an OpenAPI specification.
- Webhooks for real-time findings
- CI/CD integration to scan on every deploy
- Extremely fast: p99 < 200ms response times
https://api.artemes.ai/v1/assets/srv-01/findings \
-H "Authorization: Bearer $ARTEMES_TOKEN" \
-d "severity=critical"
"data": [
{
"id": "fnd_982hjsdf8",
"cve": "CVE-2024-21626",
"status": "critical",
"remediation_ready": true
}
]
}
Enterprise-Grade Posture
"With Artemes AI, we passed our SOC 2 audit with zero exceptions. The automatic compliance mapping saved us weeks of manual evidence gathering."
Stop triaging. Start remediating.
Breach risk compounds daily. Deploy Artemes AI in minutes and get actionable, context-aware findings instantly.