Building the future of security with NAB with Lakewatch

2026-03-24 · Source: Databricks · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Cybersecurity & Data Privacy, Data Science & Analytics · Depth: Intermediate, quick

Summary

Lakewatch, the industry's first Open Security Lakehouse, has been developed through co-innovation with organizations like NAB, a major financial institution. NAB, as one of five design partners, contributes its operational cyber defense expertise from a highly targeted sector to shape Lakewatch. This platform is designed for the AI-era, enabling advanced analytics, enterprise-wide signal correlation for sophisticated threat detection, proactive threat hunting at scale across high-volume security data, and end-to-end AI-enabled cyber defense from ingestion to response. The collaboration ensures Lakewatch is technologically advanced and grounded in real-world operational experience, aiming to provide machine-speed capabilities for modern threats.

Key takeaway

For security leaders evaluating modernizing their cyber defense infrastructure, Lakewatch offers a compelling, AI-native Open Security Lakehouse solution. Your team can benefit from a platform co-developed with real-world operational expertise from financial institutions, ensuring it addresses practical security gaps. Consider exploring Lakewatch to enhance your organization's ability to detect sophisticated threats and perform proactive threat hunting at machine speed.

Key insights

Lakewatch is an open security lakehouse co-developed with industry partners for AI-era cyber defense.

Principles

• Operational expertise is crucial for security product development.
• Open, composable architectures enhance security operations.
• AI-native design improves threat detection and response.

Method

Lakewatch's development involves deep partnership with design partners like NAB, integrating real-world cyber defense experience into a complete, turnkey security operations workflow built natively on the Lakehouse architecture.

In practice

• Implement enterprise-wide signal correlation for threat detection.
• Utilize AI for end-to-end cyber defense.
• Conduct proactive threat hunting at scale.

Topics

• Lakewatch
• Open Security Lakehouse
• AI-enabled Cyber Defense
• Threat Detection
• Security Operations

Best for: CTO, VP of Engineering/Data, Director of AI/ML, AI Security Engineer, Security Engineer, MLOps Engineer

Related on AIssential

• Your Data, Your Lake: How Observe Uses Iceberg and Streaming ETL for Observability — Lakehouse architectures can provide scalable, cost-efficient observability by centralizing diverse telemetry data.
• Built In, Not Bolted On: What AI-Native Actually Means in Cybersecurity — AI-native applications embed intelligence into their core architecture, enabling continuous adaptation and leveraging proprietary data for superior defense.
• Databricks Announces Lakewatch: New Open, Agentic SIEM — Databricks' Lakewatch offers an open, agentic SIEM built on a lakehouse architecture to counter AI-driven cyberattacks.
• MCP as the API for AI‑Native Systems: Security, Orchestration, and Scale — MCP is becoming the API for AI-native applications, requiring secure, orchestrated, and scalable deployments.
• Build an enterprise observability solution for Amazon Quick — A solution centralizes Amazon Quick operational data for comprehensive observability and natural language querying.
• 😺 OpenAI built a crypto thief — AI agents, particularly OpenAI's GPT-5.3-Codex, are highly effective at exploiting smart contract vulnerabilities.

Open in AIssential →

Editorial summary, takeaway, and curation by AIssential. Original article published by Databricks.