HQ Data Profiler

Sliq is an AI-powered data cleaning platform that transforms messy raw datasets into clean, analysis-ready data in minutes by automatically detecting and fixing common quality issues such as incorrect formats, missing values, schema inconsistencies, and formatting errors, so analysts and engineers spend less time on “janitor work” and more time on insights and modeling. It uses context-aware intelligence to understand the semantic domain of uploaded data (for example, whether it’s financial records, ecommerce logs, or medical data) and tailors a cleaning plan specifically for that dataset instead of applying one-size-fits-all rules. Users can upload files directly or integrate with workflows programmatically, and Sliq supports common data formats, including CSV, JSON, and Parquet, while seamlessly integrating into existing data ecosystems.

​Tenzir is a data pipeline engine specifically designed for security teams, facilitating the collection, transformation, enrichment, and routing of security data throughout its lifecycle. It enables users to seamlessly gather data from various sources, parse unstructured data into structured formats, and transform it as needed. It optimizes data volume, reduces costs, and supports mapping to standardized schemas like OCSF, ASIM, and ECS. Tenzir ensures compliance through data anonymization features and enriches data by adding context from threats, assets, and vulnerabilities. It supports real-time detection and stores data efficiently in Parquet format within object storage systems. Users can rapidly search and materialize necessary data and reactivate at-rest data back into motion. Tension is built for flexibility, allowing deployment as code and integration into existing workflows, ultimately aiming to reduce SIEM costs and provide full control.