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Doppel
AI defense against impersonation and social engineering
Quick facts
| Category | AI Cybersecurity |
|---|---|
| Official website | doppel.com |
| Listed on allAilists | Added November 2026 |
| Alternatives on this site | 56 in AI Cybersecurity |
What Doppel is for
Doppel is one of 57 tools in our AI Cybersecurity list. AI defense against impersonation and social engineering.
AI security tools help analysts investigate alerts, detect threats, manage identities and protect AI systems themselves. They work best as force multipliers for a team that has good telemetry already.
What to check before choosing Doppel
- Integration with your SIEM, EDR and cloud logs.
- Traceable reasoning behind each conclusion or recommended action.
- Human approval before any containment action runs.
Test on your own environment, as vendor demos use tidy data. Automated responses can disrupt production, so begin in recommend-only mode.
Doppel alternatives
Other AI Cybersecurity worth comparing with Doppel:
CrowdStrike Charlotte AI
AI security analyst
SentinelOne Purple AI
AI security operations
Google Security Operations
Security operations with Gemini
7AI
Agentic AI security operations
Burp AI
AI features in Burp Suite for pentesters
DryRun Security
AI code security reviews
Escape
AI API and app security testing
Frequently asked questions
What is Doppel?
Doppel is listed in our AI Cybersecurity directory. In short: AI defense against impersonation and social engineering. The official website is doppel.com.
What are the best alternatives to Doppel?
Popular alternatives in the same category include Microsoft Security Copilot, CrowdStrike Charlotte AI, SentinelOne Purple AI, Google Security Operations and 7AI. See all 57 AI Cybersecurity to compare more options.
Is Doppel free?
allAilists does not track prices, because AI plans change often. Check the pricing page on doppel.com for current free plans, trials and limits before you sign up.
Is Doppel safe to use for work?
Before using any AI tool for client or company work, read its privacy policy and terms, check whether your data is used for training, and confirm who owns the output. Test on your own environment, as vendor demos use tidy data. Automated responses can disrupt production, so begin in recommend-only mode.
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