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Open-source desktop app for running AI chat models locally or via APIs, as a private ChatGPT alternative.
AI-driven network detection and response platform that identifies and stops identity-based and lateral-movement cyberattacks in real time.
Developer-first security platform unifying code, cloud, runtime and AI pentesting with noise reduction and autofix.
Compliance automation platform that continuously monitors controls and evidence to help companies achieve SOC 2, ISO 27001, and HIPAA.
Cloud DLP and CASB that classifies and protects sensitive data across SaaS apps using deep learning (now Palo Alto Networks).
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No public pricing
No public pricing
- ✦Run open-source LLMs locally
- ✦Connect to online models (OpenAI, Claude, Gemini)
- ✦Private, offline-capable AI chat
- ✦Open source and self-hostable
- ✦Model library via Hugging Face
- ✦Cross-platform desktop app
- ✦Real-time AI-driven threat detection beyond traditional EDR
- ✦Detection of identity-based attacks and lateral movement
- ✦360 Response for enforced containment across identity, devices, and network
- ✦Exposure management and security posture improvement tools
- ✦Managed detection and response (MXDR/MDR) services
- ✦Integrations across existing security tool ecosystems
- ✦Attack Labs research sharing threat intelligence and techniques
- ✦SAST, SCA and secrets scanning
- ✦Cloud misconfiguration (CSPM) and container scanning
- ✦AI-powered autonomous pentesting
- ✦AutoFix pull requests and auto-triage
- ✦Runtime and bot protection (Zen)
- ✦SOC 2 and ISO compliance support
- ✦Continuous automated compliance monitoring across frameworks
- ✦Automated evidence collection and audit preparation
- ✦Personnel access and permissions management
- ✦Vendor and third-party risk assessment workflows
- ✦Automated security questionnaire responses
- ✦Public-facing trust center for compliance status
- ✦400+ tool integrations and an API for custom workflows
- ✦Deep-learning data classification (99.5% claimed accuracy)
- ✦Cloud DLP across SaaS applications
- ✦One-click deployment across apps, devices and users
- ✦End-user self-remediation of violations
- ✦Broad SaaS integrations
- ✦Insider-threat and breach monitoring
- →Private local AI chat
- →Using multiple models in one app
- →Avoiding cloud data sharing
- →Experimenting with open models
- →Security operations teams needing detection beyond EDR/SIEM gaps
- →Enterprises defending against identity-based and hybrid cloud attacks
- →Organizations needing managed threat detection and response services
- →Finance, healthcare, and public sector teams meeting compliance-driven security needs
- →Finding and fixing code vulnerabilities
- →Securing cloud and containers
- →Running continuous pentests
- →Automating compliance evidence
- →Preparing for and maintaining SOC 2 or ISO 27001 certification
- →Automating responses to customer security questionnaires
- →Managing vendor security reviews at scale
- →Centralizing risk management across a growing company
- →Prevent data leaks across SaaS apps
- →Classify and monitor sensitive data
- →Reduce breaches from human error
- →Give security teams cloud data visibility