Problem

Security operations teams are overwhelmed by alert volume, false positives, fragmented data, and labor-intensive work such as log stitching, user validation, and ticket management. That consumes scarce, expensive analyst capacity and slows response to genuine threats; for smaller organizations, building an effective SOC internally also carries substantial cost and complexity. Exaforce’s main use case is to reduce the alert firehose to high-confidence findings, then accelerate the investigation and response to the threats that matter.

Product / Service

Exaforce offers an AI-native Agentic SOC Platform that combines a multi-model AI engine and data-exploration fabric with specialized Exabots covering detection, triage, investigation, and response. The agents operate across identity, cloud, endpoint, and SaaS data, enriching and validating alerts, correlating activity across environments, supporting natural-language investigation and threat hunting, and automating response workflows. Customers can use the platform as hosted SaaS or self-host it, or have Exaforce operate it as a fully managed MDR service. The value proposition is greater coverage and faster, more consistent response without proportionally adding analysts or building a SOC from scratch.

Market

Exaforce competes in the emerging AI-native or agentic SOC market, overlapping with SIEM, XDR, SOAR, and managed detection and response providers. Its stated competitive set includes Google Security Operations, CrowdStrike Falcon with Charlotte AI, Palo Alto Networks Cortex XSIAM, Splunk Enterprise Security, and Microsoft Security Copilot; these products generally approach the problem from large SIEM, endpoint, security-platform, or security-copilot ecosystems, while Exaforce emphasizes full-lifecycle automation and real-time data exploration.

The company appears to have commercial customer traction rather than being merely pre-revenue. It announced a $75 million Series A in April 2025 and a $125 million Series B in May 2026, and its public case studies identify customers including Fuze and Forcepoint. Reported outcomes include investigations reduced from hours to minutes, 95% of alerts auto-triaged as verified false positives, 14-minute P0 mean time to respond, and 100% alert-category coverage; the available evidence does not disclose revenue or customer-count figures, so the scale of traction cannot be quantified financially.