Zandra AI specializes in Digital Forensics and Incident Response (DFIR) by leveraging advanced techniques to analyze and correlate data from a wide range of sources. Its primary goal is to quickly assist investigators by analyzing forensic artifacts and activity logs from client PCs, mobile devices, firewalls, servers, and other security subsystems. Zandra uncovers logical connections between events and contextual meaning in communications, providing crucial insights into what occurred. It acts as a helper for investigators or incident responders, enabling the analysis of vast quantities of data at scale and linking events together. To ensure compatibility with its AI, Zandra normalizes all forensic data to specific formats, supporting common Microsoft Office formats (.DOCX, .XLSX, .PPTX, etc.), text-based formats (.TXT, .CSV, .JSON, .HTML, .PDF), and converting email containers (.PST/.OST) to .PDF or .TXT. Database data can be imported directly into Zandra's built-in MySQL or converted to .CSV or .XLS for processing by its integrated vector database. Data can be provided directly to Zandra or follow the workflow with Paraben’s E3 Platform to produce compatible data. While Zandra AI efficiently cross-correlates and analyzes data, the forensic examiner remains responsible for verifying results and ensuring compliance with legal standards. This first-party knowledge is essential for court testimony, as the examiner must demonstrate personal analysis and confirmation of findings. Zandra is designed to act as a team member, guiding examiners to valuable information. The integration of AI in DFIR labs presents significant opportunities, and Zandra offers a customizable policy template to assist labs in seamlessly integrating AI responsibly, addressing data handling, ethical considerations, validation procedures, and legal requirements.

Features & Benefits

• Comprehensive Data Source Processing
  • Analyzes and correlates data from a wide array of sources, including logs, firewalls, routers, computers, internet data, email, registry, files, smartphone data, messaging, apps, user data, and cloud data.
• Advanced Data Normalization
  • Ensures compatibility with AI by normalizing forensic data to specific formats, supporting common Microsoft Office, text-based, and database formats. Facilitates conversion of email containers and integration with Paraben’s E3 Platform.
• Flexible Deployment Options
  • Available in 100% cloud deployment with multi-layered security (vector database obfuscation, multi-factor authentication, encryption, private Groq cloud) or local machine deployment with data residing in an obfuscated vector database and Validian encryption. Supports both local and cloud processing for AI.
• Robust Data Security & Privacy
  • Employs robust data storage and security mechanisms, including encrypted vector databases, encrypted MySQL databases, and secure transmission to a private cloud. User chat logs and provided document text are explicitly excluded from any AI model training, ensuring privacy. Anonymous telemetry excludes identifying content.
• Customizable Reporting
  • Allows users to generate outputs based on prompts (e.g., HTML timelines) and can reference back to source data from Paraben's E3 platform if uploaded as the source.
• Multi-Language & Unique Data Understanding
  • Understands 160 different languages and can accept prompts in any mix of these. Also comprehends unique data such as emojis when reviewing information.
• Evidence-Based & Private AI
  • Designed to follow rules of evidence, keeping all case data private, isolated, and obfuscated. Trained on common digital forensics and incident response data types to understand unique investigation data in context, ensuring data privacy and relevance unlike other AI platforms.