Darwin
Uses reinforcement learning to continuously improve agent resilience by observing real attacks and policy violations from production data.
Picari insights
Mid-market to enterprise engineering and security teams running autonomous AI agents in production who need automated, adaptive runtime hardening against evolving adversarial attacks.
- Dynamic hardening of production autonomous agents
- Adaptive defense against novel LLM jailbreaks and prompt injections
- Automating agent guardrail updates from real-world telemetry
- Static LLM deployments (e.g., basic search or fixed Q&A bots)
- Air-gapped systems or environments that prohibit production telemetry feedback loops
- Organizations seeking basic, signature-based web application firewalls (WAFs)
Ask about pricing, alternatives, or if Darwin is right for you.
- Personalized fit analysis
- See relevant alternatives
- Run an evaluation when you're ready
Things to consider
Every product has trade-offs, and which of them matter depends on your environment, your team and your timeline.
Vijil Darwin pricing and integrations
For Vijil Darwin integration and pricing details, ask Picari. Start a briefing with your question, such as whether it connects to your SIEM, identity provider and ticketing stack, or how it is priced at your seat count and data volume.
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Are you from Vijil? Verify this profileProfile last updated on 27 September 2026 by Picari.