Security operations leaders have invested in SIEM platforms, SOAR automation, and threat intelligence integration to address this problem. Those investments have made real improvements. What they haven't solved is the fundamental data fragmentation problem: when the authoritative version of an investigation-relevant question requires joining data across systems that weren't designed to talk to each other, the analyst becomes the integration layer.

Genie serves as the agentic interface within Lakewatch, leveraging the advanced reasoning of Anthropic Claude models to deliver agentic security operations. By integrating Claude’s reasoning capabilities, Lakewatch can correlate complex signals across security, IT, and business data in seconds. This allows analysts to deploy defensive security agents that don't just search for data, but understand the context of the investigation to surface high-fidelity threats faster than manual workflows ever could.

Genie serves as the agentic interface within Lakewatch, allowing analysts to pivot from human-in-the-loop to human-at-the-helm. Instead of writing complex SQL or learning proprietary search languages, analysts use Genie to orchestrate autonomous agents that can hunt, summarize, and cross-reference petabytes of data in seconds.

Genie enables security operations teams to ask investigation questions in natural language across their full security data environment. An analyst can ask: 'Show me all authentication events for user X in the past 7 days, the systems they accessed, any associated file access events on sensitive data stores, and any related alerts from our EDR.' That investigation synthesis surfaces in a single conversational response.