Orqle.ai takes its name from the “orcs” of legend—creatures known for their skill in navigating dark, hidden places with confidence and precision. Just as orcs venture into shadowy realms, Orqle.ai excels at locating and understanding data in “dark spaces”—those unindexed, metadata-poor data silos that are challenging to explore. These dark spaces are bounded and secure, safely isolated from the risks of internet-based language models (LLMs) that may pose privacy concerns. With Orqle.ai, users gain a powerful data solution that ensures privacy and security without reliance on external networks, making it ideal for organisations with sensitive or regulated data.
Orqle.ai is an ArQiver add-on for advanced data exploration and migration engine that simplifies the management and modernization of vast data collections. Designed for seamless migration and deep data exploration, Orqle.ai preserves the integrity of each data asset while fully adhering to national and EU data standards. Purpose-built to recognize and retain metadata, document structures, and unique features like watermarks and signatures, Orqle.ai offers a robust and trustworthy solution for comprehensive data handling.
Transitioning data from legacy formats to modern digital environments requires precision to retain original integrity. Orqle’s advanced capabilities streamline this process with care, using AI and automation to preserve essential metadata and document context, ensuring each data set’s unique characteristics remain intact. Equipped with strict data integrity protocols and layered backups, Orqle ensures data is securely transferred, unaltered, creating a reliable digital reflection of the original material. Orqle’s multi-layered security, including version control, allows for quick restoration if needed, preserving the authenticity of all data. This structured approach empowers organisations to modernise data collections while maintaining authenticity and reliability, making data more accessible and relevant for contemporary applications.
Orqle’s flexible architecture offers a suite of powerful tools for data exploration, classification, pattern recognition, and dark data discovery. Key features include:
Orqle.ai provides three tailored processing modes — metadata-only, full context (metadata and content), and content-only — to ensure only relevant data is processed, optimising cost and compliance. For “dark data” with minimal metadata, Orqle.ai employs a targeted sampling approach to efficiently locate and analyse hidden information, maximising resource allocation.
Leveraging a microservice-based architecture, Orqle.ai dynamically adjusts hardware resources to fit task requirements, providing substantial cost savings and faster processing than traditional VM solutions.
Orqle’s unsupervised analysis enables users to identify distinctive characteristics within data segments, even within dark data. Users can assign labels, filter data, and integrate custom classification tables, producing valuable datasets ready for advanced analysis and model training.
Through Orqle’s interactive visualisations, users can quickly recognize patterns and intuitively explore data, avoiding the need for repeated reprocessing. Python integration further enhances flexibility for external AI model integration, expanding application possibilities while maintaining security.
Based on data quality and project goals, Orqle.ai can be used independently or in combination with AI to unlock deeper insights. For specialised or context-sensitive data, Orqle.ai provides a strong foundation for initial exploration, particularly in uncovering and analysing dark data, ensuring optimal accuracy and effectiveness. With Orqle.ai, organisations can securely digitise, explore, and organise their data while maintaining authenticity and compliance. This future-ready, privacy-focused solution is suited to both legacy and modern data, protecting sensitive information from external risks.