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Analysis · Enterprise Software & IT

Aquila I introduces security data lakehouse for autonomous cyber defense

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Date
Company
Aquila I
What it does
AI-native cyber defense platform
Kind
Analysis
Sector
Enterprise Software & IT

What they do

Aquila I builds AI-native cyber defense platforms that combine data lake and warehouse capabilities for cybersecurity operations

What happened

The company's white paper outlines a five-stage architecture for autonomous security operations using real-time analytics and AI-driven detection

Why it matters

Traditional cybersecurity platforms are falling short due to fragmented data and lack of real-time processing, which Aquila I aims to address with its…

The details

  • Aquila I has introduced a new concept called a 'security data lakehouse' in its white paper, which combines the scalability of a data lake with the structured analytics of a data warehouse.
  • The lakehouse is designed specifically for cybersecurity operations, acting as the operational backbone of an autonomous Security Operations Centre (SOC).
  • The architecture enables unified telemetry ingestion, real-time analytics, AI-driven detection, automated response workflows, and long-term forensic retention.
  • The white paper outlines a five-stage architecture for autonomous security operations, starting with telemetry ingestion from endpoints, servers, cloud infrastructure, and network devices.
  • Data is normalized into structured formats like OCSF, allowing previously disconnected systems to operate within a common framework.
  • Machine learning models, behavioural analytics, and stream-processing engines continuously analyse telemetry in real time to identify anomalies and emerging threats.
  • Automation is presented as a force multiplier that reduces repetitive workloads, allowing security teams to focus on strategic investigation and decision-making.
  • The final layer acts as a centralized cyber command centre, providing unified visibility, governance controls, and coordinated response orchestration across the enterprise.

The bigger picture

  • Traditional analytics systems are not built for the adversarial nature of cybersecurity, requiring real-time processing and massive telemetry scalability.
  • During active attacks, even small delays in detection can allow adversaries to move laterally, escalate privileges, or exfiltrate sensitive information.
  • Attackers increasingly target the security data itself by attempting to delete logs or manipulate forensic evidence.
  • The report emphasizes immutability, long-term retention, and verifiable audit trails as foundational infrastructure requirements.
  • AI systems are only as reliable as the quality of the data feeding them, making clean, normalized, context-rich datasets essential for effective AI-driven cybersecurity.

About the business

  • Aquila I builds AI-native cyber defense platforms that combine data lake and warehouse capabilities for cybersecurity operations.
  • The company's platform is designed to act as the operational backbone of an autonomous Security Operations Centre (SOC).
  • The platform enables unified telemetry ingestion, real-time analytics, AI-driven detection, automated response workflows, and long-term forensic retention.
  • The architecture is designed to support autonomous security operations at enterprise scale.
  • The company's white paper outlines a five-stage architecture for autonomous security operations.

The deal

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