Industry Outcomes: Security teams responding to thousands of alerts per day aren't doing security analysis. They're doing alert triage. The real threats are the ones that don't look like alerts.
by Taylor Kain
USE CASE
Threat Intelligence & Security Analytics at Scale
Security operations centers in enterprise organizations are managing alert volumes that have grown far beyond what human analysts can meaningfully process. The average enterprise SOC receives tens of thousands of alerts per day. The response to that volume is prioritization — which means the alerts that don't make the priority threshold don't get investigated. And sophisticated threat actors know exactly how to operate below that threshold.
Alert fatigue isn’t just an analyst problem; it’s a data architecture problem. Traditional SIEMs force a ‘collect and discard’ mentality—a proprietary 'security tax' that limits visibility due to spiraling costs. When security telemetry is fragmented across endpoint, network, identity, and cloud logs, the only way to correlate signals is through a manual, exhausting analyst process. In this siloed environment, the sheer volume of data inevitably overwhelms human capacity, creating the gaps that sophisticated threat actors exploit.
A CISO managing enterprise security operations needs two things that current security tooling frequently can't provide simultaneously: complete coverage of the threat surface, and the analytical fluency to identify genuine threats within that coverage quickly enough to contain them before material damage occurs.
The breach that costs the company the most is never the one that generated the most alerts. It's the one that generated signals that nobody had time to correlate.
The open agentic SIEM replaces the manual bottlenecks of the past with unified, machine-speed defense. Lakewatch serves as the foundation, eliminating security silos by unifying 100% of your security, IT, and business telemetry on an open lakehouse architecture. By leveraging Agent Bricks and automated OCSF normalization, Lakewatch automates the heavy lifting of data wrangling and alert triage. This allows Databricks Genie to act as a high-fidelity AI security agent, enabling leaders to interrogate the full environment in natural language. A CISO can ask: ‘Which user accounts have shown lateral movement patterns in the past 72 hours, correlated with recent privileged access changes?’ In an open agentic system, this doesn't just return a list—it triggers autonomous agents to hunt, summarize, and neutralize threats at machine speed.
The security organizations that will most effectively defend their enterprises in the current threat environment aren't necessarily the ones with the most tools or the largest SOC headcount. They're the ones that can extract meaningful signals from 100% of their telemetry at the speed that modern threats require. Lakewatch and Genie don't just replace manual security tasks; they transform the role of the defender from a “human-in-the-loop” to a “human-at-the-helm” model. By leveraging an open agentic SIEM, security leaders are no longer bogged down by the "heavy lifting" of data normalization and triage. Instead, they orchestrate a swarm of AI agents that hunt and neutralize threats autonomously, allowing the human expert to focus on high-level strategy and decisive response.
LAKEWATCH · KEY DIFFERENTIATORS
Transform your SOC with unlimited, unified data, petabyte scale and swarms of agents
Defend at Machine Speed with Lakewatch
The era of the proprietary "Security Tax" is over. See how Lakewatch and the open security lakehouse approach are helping organizations unify 100% of their telemetry and deploy AI agents to detect threats at scale. Lakewatch is currently available in Private Preview.
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