Digital forensics today is slow and manual. At Ilexum Group, we use AI and standardized processing to analyze evidence, find correlations, and generate court-ready reports instantly, reducing time.
Current Status
We have developed a functional platform with a working backend (Processor) and a visual UI for case and evidence analysis. Core features such as evidence standardization, processing pipelines, and AI-based correlation are implemented. We are currently refining the product, improving usability, and preparing for pilot testing with real-world forensic cases and potential partners in the legal and cybersecurity sectors.
Problem or Opportunity
Digital forensic investigations are slow, manual, and difficult to scale. Experts must analyze large volumes of heterogeneous data from devices like computers, mobile phones, and storage systems using multiple tools. Correlating evidence with legal claims, maintaining chain of custody, and generating reports requires significant time and effort, often taking days or weeks per case. This creates bottlenecks, increases costs, and limits the number of cases an expert can handle.
Solution (product or service)
We provide a next-generation digital forensics platform that standardizes evidence ingestion and automates analysis. By integrating tools like Tractium, Bitex, and Evidex, we structure all evidence into a unified model. Our AI layer correlates data across entire cases, detects relevant patterns, and extracts actionable insights. The platform also includes a visual interface for evidence exploration and automatically generates court-ready forensic reports, including technical findings and chain of custody.
Business model
We are evolving toward a SaaS business model targeting digital forensic experts, consulting firms, and legal organizations. In the meantime, the platform is already being used internally, I am an active user. This allows continuous validation, rapid iteration, and real-world testing, ensuring the product becomes highly refined before external release. At the same time, this approach enables early revenue generation and partial self-funding, reducing initial capital requirements while accelerating product maturity.
