Semantic Search Engine
Advanced AI that understands context, intent, and relationships between concepts
- Natural language query processing
- Context-aware threat correlation
- Multi-language semantic understanding
- Relationship graph mapping
Explainability AI
Complete transparency into AI decision-making processes
- Decision tree visualization
- Confidence scoring breakdown
- Factor attribution analysis
- Audit-ready reasoning trails
Multi-Tenant Architecture
Enterprise-grade security with complete data isolation
- Zero-trust access controls
- End-to-end encryption
- Tenant-level data isolation
- SOC 2 Type II and GDPR assessments pending
Real-Time Processing
Lightning-fast analysis and monitoring of your data streams
- Sub-second threat detection
- Streaming data pipeline
- Live dashboard updates
- Instant alert notifications
Continuous Monitoring
24/7 surveillance of your critical assets and data flows
- Dark web forum scanning
- Marketplace monitoring
- Data breach detection
Universal Integration
Seamlessly connect with your existing infrastructure
- REST and GraphQL APIs
- SIEM/SOAR connectors
- Webhook event streaming
- Pre-built security tool integrations
Product demo · Simulation
Watch one alert go from found to taken down.
A short, narrated walk through DarkOnion with a fictional company: spotted, explained, checked, approved, taken down and verified.
6 chapters · about 1½ minPress play, or step through at your own pace.
Read the demo as text
- Watch. Sam’s watchlist is ready. DarkOnion looks for what is yours. 1 of 14 new mentions matches. One alert, not 14 mentions. Sam opens the in-app alert. Alerts arrive inside the app.
- Explain. The alert says what happened. Your CFO’s work login is for sale. It shows why it flagged this. Plain reasons you can judge. Sam checks the score, then the proof. No black box.
- Check it. Sam reads the original post. The real post, not a summary. Sam writes down why. Anyone can follow the decision later. Sam marks it as real. Logged with Sam’s name and time.
- Ask. Sam asks: is anyone else exposed? Plain English. No query language. The assistant finds ops@ exposed too. A clear answer, not search results. It lists the findings it used. You can check each claim yourself.
- Approve the AI. An AI investigation does the legwork. Less manual work for your team. It stops before changing anything. The AI can’t change your setup alone. Sam approves, then resumes the run. A person stays in charge.
- Takedown 1/4: What to remove. Sam starts a takedown from the finding. It stays linked to the alert. Sam pastes the address to remove. You decide exactly what to target.
- Takedown 2/4: Check & prepare. DarkOnion checks for open requests. Only one open request per target. Sam adds the evidence. You choose what the site sees. Sam adds a short reason. It helps the site decide.
- Takedown 3/4: Get approval. Sam names Maya in Legal as approver. You set the approval per request. Sam records Maya’s yes in one step. It shows who approved, and when.
- Takedown 4/4: Send & confirm. Sam’s team sends the request. Your team stays in control. Days later, Sam checks the page. The hosting site decides on removal. Sam records: Removed. Takedown closed. The result is checked, not assumed.
Screens simplified and steps combined for this demo. Example Financial Co., its people and domains are fictional. Any resemblance to real companies or people is coincidental.