The startup develops a cybersecurity data infrastructure platform that integrates a semantic engine with existing systems, enabling real-time insights through an agent-based interface. This technology enhances the ability of security teams to create and scale modular security applications and analytical capabilities, addressing the challenges of managing diverse security architectures.
Funding
$5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Security teams must continuously ingest, normalize, and analyze heterogeneous log streams from thousands of sources, a process that is labor‑intensive, error‑prone, and often leaves blind spots. Traditional SIEMs struggle with evolving log formats and generate high alert fatigue, delaying response to critical incidents. Maintaining complete data retention while scaling to enterprise volumes adds further operational complexity.
Solution
Ziggiz delivers a cloud‑native data lakehouse that automatically ingests raw events from any log source, regardless of format, and stores them in a unified, schema‑on‑read repository. The platform applies a semantic enrichment layer to translate disparate logs into a consistent data model, enabling real‑time, definition‑based alerts without the overhead of traditional SIEM rule sets. By preserving 100 % of the original data, analysts can perform ad‑hoc queries and forensic investigations without costly re‑normalization. Integrated analytics run on a Databricks‑powered engine, providing scalable processing and machine‑learning‑ready datasets for proactive threat detection. Alerts and insights are delivered through a web dashboard and API, allowing seamless integration with existing security workflows and incident‑response tools. The solution reduces manual data handling, shortens time‑to‑investigation from months to minutes, and supports compliance by retaining the full audit trail.
Target Audience
The primary customers are security operations centers and SOC analysts in large enterprises, government agencies, and regulated sectors such as healthcare, who need to consolidate and act on high‑volume, heterogeneous log data. Ziggiz also serves security vendors and data‑centric organizations requiring a scalable, cloud‑native analytics foundation.
Features
- Automated ingestion pipeline supporting thousands of log sources, edge devices, and custom formats via native connectors and API ingestion
- Schema‑on‑read semantic layer that normalizes data into a unified model without altering the original events
- Definition‑based alert engine that generates low‑noise, context‑aware notifications using customizable rule definitions
- Scalable analytics powered by Databricks, enabling real‑time queries, ML model training, and batch processing on petabyte‑scale data
- Full data retention with immutable storage, ensuring complete auditability and compliance reporting
- Web‑based dashboard with interactive visualizations, drill‑down capabilities, and role‑based access controls
- RESTful and FHIR‑compatible APIs for integration with SOAR platforms, ticketing systems, and existing SIEMs
- Built‑in security controls including end‑to‑end encryption, IAM policies, and audit logging