Evaluating Exaforce as an AI SOC platform

If Exaforce is on your shortlist of AI SOC tools, a useful evaluation goes past the feature list and into how the platform reaches a verdict. This post walks through the architecture, the deployment options, and published customer results so you can test each one against your own requirements.

What Exaforce does

Exaforce is an agentic SOC platform and managed detection and response (MDR) service that automates detection, triage, investigation, and response. It covers identity, IaaS, SaaS, endpoint, email, and insider threats. High-growth companies often use it to replace a traditional SIEM, SOAR playbooks, and an outsourced MDR or MSSP contract at once. Mid-market enterprises with an established SIEM usually start by running Exaforce alongside it.

How the AI works

The work is done by Exabots, task-specific AI agents assigned to each stage of the SOC workflow. The five agents are Exabot Detect, Exabot Triage, Exabot Investigate, Exabot Respond, and Exabot Hunt.

Exabots reason over Multi-Model AI rather than raw log text. The Semantic Model maintains a living map of the entities and relationships in your environment. The Behavioral Model learns normal activity across human and machine identities, applications, data, resources, and locations. The Knowledge Model then synthesizes that context into findings an analyst can act on. Splitting the work this way addresses the problems LLM-only tools run into on long investigations, namely limited memory, inconsistent reasoning between runs, and cost that climbs with data volume.

Underneath sits the Data Platform, which handles real-time ingest, deduplication, normalization, and correlation, with storage tiering to keep retention costs in check. Analysts query logs, identity, configuration, code, and threat intel through the Advanced Data Explorer in natural language, a style of work Exaforce calls vibe hunting. ExaGo, launched in July 2026, brings voice-driven SOC work to mobile.

Deployment options

Your own team can run the platform, or you can hand day-to-day operations to Exaforce MDR, a 24/7 managed service that runs the same Exabots. Because both options sit on the same platform, moving between them does not mean changing tools or rebuilding detections.

What customers report

Accton cut mean time to investigate (MTTI) by 94%, from 3 hours to 10 minutes, and saved $300K+ a year by avoiding added SOC headcount. Forcepoint reports a 14-minute mean time to respond (MTTR) on P0 incidents, with 95% of alerts auto-triaged as verified false positives, after replacing a legacy MSSP. Guardant Health used Exaforce to disprove a suspected AWS account compromise in about 15 seconds during a live incident.

How to run your evaluation

Start with the alert types that cost your analysts the most time today and measure MTTI before and after. Open a few closed investigations and check whether the evidence behind each verdict is clear enough that a senior analyst would sign off on it. Confirm that the attack surfaces you care about most are covered from day one, and ask how analyst feedback is used to tune detections over time.

A good AI SOC should make your team faster without asking them to trust a black box. That is the bar to hold Exaforce to, and every other platform you consider.