ReliaQuest vs. Google SecOps
GreyMatter is an agentic AI security operations platform that unifies detection, containment, investigation, and response across your entire stack, achieving threat containment in under 5 minutes. Google SecOps is a cloud-native SIEM backed by Google's infrastructure and Mandiant threat intelligence, but choosing it means replacing your current SIEM with a proprietary ecosystem where detection rules, data models, and AI capabilities are locked to Google's platform. For enterprise security teams that need technology-agnostic, agentic AI across the full TDCIR lifecycle, GreyMatter is the stronger fit.
GreyMatter Agentic AI
Google SecOps is a cloud-native SIEM that consolidates detection, investigation, and response into Google's ecosystem. Choosing it requires a full SIEM replacement: migrating all data, detection rules, and workflows to their platform. All detection rules must be written in YARA-L 2.0 and data normalized to Google's proprietary Unified Data Model, locking your investment to a single vendor's formats.
ReliaQuest GreyMatter is an agentic AI security operations platform covering detection, containment, investigation, response, CAASM, digital risk protection (DRP), data pipeline management, and phishing analysis, all unified under a single architecture. Moves your team from reactive alert handling to proactive and predictive security operations.
Alert Triage and Investigation Agents remain in "public preview" (not generally available) with no published accuracy metrics or validation methodology. Google is offering a no-cost trial through June 2026, underscoring the pre-production status. No documented self-service interface for managing what the AI knows about your organization. When your environment changes, you may not be able to update the AI's understanding directly.
Six Agentic Teammates that leverage 200+ agent skills and 400+ AI tools, each purpose-built for core security functions. ReliaQuest GreyMatter achieves 99.4% investigation accuracy validated through a 7-standard lifecycle. Customer-controlled Agentic Memory for viewing, editing, and managing AI guidelines directly. Agentic automated response playbooks execute containment autonomously across your full stack.
Detection runs only after data is ingested, parsed, and normalized into Google's data lake. No at-source or in-transit detection, so threats can only be identified after full data collection, adding latency. AI investigation capabilities have not reached general availability. Your SOC would depend on an unproven capability for one of its most critical functions.
Fully autonomous SOC lifecycle across EDR, IAM, email, cloud, and network, achieving threat containment in under 5 minutes. Investigates and responds to 74M alerts annually, 100% by AI. 57+ open source and paid threat intelligence feeds leveraged by Agentic Teammates, turning threat data into predictive insights. The GreyMatter Mobile App enables investigation, triage, and response from anywhere.
Requires full SIEM replacement and migration of all data, detection rules, and workflows to Google's platform. Data must be normalized to Google's proprietary Unified Data Model. Once your team has invested in building detection content in YARA-L 2.0 and UDM, switching vendors means rewriting everything from scratch.
250+ data sources with bidirectional APIs. GreyMatter is technology-agnostic: it integrates with your existing tools regardless of vendor, preserving your current investments rather than forcing ecosystem lock-in. Universal Translator auto-onboards custom and proprietary sources, no manual parsing or professional services required.
All detection logic compiled to YARA-L 2.0, a language used only in Google SecOps. While Gemini can assist with natural language rule creation, the underlying rules remain locked to Google's format. If you leave the platform, every detection must be rebuilt from scratch. Detection runs only against data already ingested into Google's data lake.
Independent detection engine: 2000+ curated rules, at-storage, at-source, and in-transit coverage. Detection Engineering Teammate autonomously tunes rules and creates custom detections, or your team can build your own using natural language. Ingests and investigates alerts from your existing vendor tools and custom rules.
Attack surface management available through Mandiant (separate product, separate licensing), not natively embedded in Google SecOps. Digital risk protection and phishing analysis require additional third-party tools. Growth through acquisition adds ingestion costs and migration complexity.
Unified visibility across IT, OT, and multi-cloud environments with multi-entity support. GreyMatter Discover maps and monitors your complete attack surface.
Full SIEM replacement requiring data migration, detection rule rewriting in YARA-L 2.0, and workflow rebuilding. Multi-month transition during which your security operations are at risk. Advanced customization requires paid Mandiant consulting, positioned as an upsell for program transformation, custom detection development, and tailored operational guidance.
AI is trained on nearly two decades of operational experience across 1,300+ complex environments. Data onboarding, custom parsing, rule tuning, and custom detections included. Your team retains full operational control.
Tiered pricing with ingestion ceilings. As you add log sources, increase logging fidelity, or grow through acquisition, you risk exceeding your licensed tier and facing step-up costs or forced data filtering. Attack surface management, digital risk protection, and phishing analysis require separate products and licensing beyond the base platform.
Core platform priced per endpoint and expansion capabilities priced by scope. No token-based pricing for AI usage. At-source and in-transit detection save customers an average of 3.5M annually on SIEM dependency and 900K annually on tool fragmentation. Delivers 224% three-year ROI (Forrester TEI, 2025).
Backed by Google's cloud infrastructure. However, proprietary lock-in creates long-term scaling risk: all detection content in YARA-L 2.0 and data normalized to UDM means your investment is non-portable. Growing through acquisition adds ingestion costs and migration complexity.
Backed by 100+ patents and 94% customer retention, with SOC 2 Type 2, ISO 27001, PCI DSS, and HIPAA certifications. FedRAMP In Process.
AI investigation capabilities remain in public preview with no published accuracy metrics or validation methodology. No documented self-service interface for managing the AI's accumulated knowledge about your organization. AI only investigates alerts within Google SecOps, not across your broader security stack.
Agentic Memory lets analysts view, edit, and delete the AI's operational guidelines. Hallucination risk is mitigated through Retrieval-Augmented Generation (RAG), which grounds every AI response in historical security data. Utilizes a 7-standard AI testing and validation lifecycle: expert validation, crowdsourced QA, daily statistical sampling, golden dataset testing, LLM-as-judge evaluation, transparency artifacts, and built-in safety guardrails.
The ReliaQuest Difference
Built by Practitioners,
Trained on Reality
GreyMatter is built on decades of cybersecurity operations experience, using insights from various industries, attacks, technologies, and geographies across 1,300+ real customer environments. Our AI is designed and maintained by former and current SOC operators, including detection engineers, threat hunters, and incident responders.
An Agentic System.
Not Task Bots.
Standalone AI agents perform one well-defined task. GreyMatter uses task agents as skills under an agentic system. These agentic systems function as personas that reason across alerts, detections, hunts, threat intelligence, and exposures—using more than 200 agent skills and 400 AI tools to achieve a defined result.
Extensive
Validation Process
Active engineers and cyber experts continuously guide and refine AI behavior with guardrails, human QA/QC, and feedback loops that improve accuracy over time. Human-in-the-loop governance ensures trust and reliability.
Platform
Capabilities
GreyMatter is AI integrated with a security operations platform, including native capabilities like attack simulation, CAASM, and dark web monitoring that AI uses for additional context.
Multi-Model
Approach
GreyMatter uses a model-agnostic AI layer that selects the most effective model for each task—based on use case, data type, and performance requirements. Better outcomes, not model dependency.
7 Questions That Separate GreyMatter from Google SecOps
The differences that matter most when your SOC needs a platform that layers onto your existing stack, not a full SIEM replacement that demands migration, rule rewrites, and vendor lock-in. Here's how GreyMatter compares.
Google SecOps is a full SIEM replacement. All existing detection rules must be rewritten in YARA-L 2.0, data normalized to Google's proprietary Unified Data Model, and workflows rebuilt. This is a multi-month project during which your detection coverage is at risk. GreyMatter integrates with your existing SIEM as an overlay with no replacement, migration, or rule rewriting required.
GreyMatter's Agentic Teammates handle 100% of Tier 1/2 investigations autonomously at 99.4% published accuracy, processing 74M alerts annually. Google SecOps' Alert Triage and Investigation Agents remain in public preview (not generally available) with no published accuracy metrics. Google is offering a no-cost trial through June 2026, underscoring the pre-production status.
GreyMatter's Detection Engineering Teammate creates rules that deploy across all 250+ integrated technologies. Customer-authored rules receive the same AI investigation as ReliaQuest-authored rules. Google SecOps detection logic is compiled to YARA-L 2.0, which runs only within Google's ecosystem. If you leave the platform, every detection must be rebuilt from scratch.
GreyMatter is priced per endpoint with no token-based pricing. At-source and in-transit detection reduce SIEM ingestion costs. Google SecOps packages include ingestion ceilings. As you add log sources or grow through acquisition, you risk exceeding your licensed tier, facing step-up costs or forced data filtering to stay within limits.
GreyMatter includes GreyMatter Discover, Digital Risk Protection, Phishing Analyzer, and Threat Risk Scoring natively. Google SecOps requires Mandiant (separate product, separate licensing) for attack surface management, and third-party tools for digital risk protection and phishing analysis.
GreyMatter's Agentic Memory provides a self-service interface to view, edit, and delete the AI's operational guidelines directly. Google SecOps has no documented self-service interface for managing what the AI knows about your organization. When your environment changes, you may not be able to update the AI's understanding directly.
GreyMatter normalizes data to OCSF, an open industry standard, ensuring portability. Detection rules deploy across all integrated technologies. Google SecOps normalizes data to its proprietary UDM and requires rules in YARA-L 2.0. Once you've built detection content in these formats, switching vendors means rewriting everything from scratch.
Download the complete guide with the right questions to ask when evaluating AI SOC vendors.
Built to Run in Your SOC,
Not Just Win in a Demo
GreyMatter is the agentic AI security operations platform built from inside security operations, informed by 15+ years of expertise across 1,300+ customer environments.
GreyMatter is production-ready, with six AI personas that use over 200 agent skills and 400 AI tools to work toward objectives across the full SOC workflow—not just isolated tasks.
Learn How GreyMatter Agentic AI Scales Your Security Operations
GreyMatter is an agentic AI security operations platform with 6 agentic Teammates that use hundreds of agent skills and AI tools to work toward an objective, not just tasks.
