# Key Differentiators Radiant is built on a different premise than the tools most security teams have relied on. While legacy SIEM tools generate alerts and stop there, and most AI SOC platforms cap out at a handful of pre-trained scenarios, Radiant triages every alert across your entire stack: known threats, unknown threats, and everything in between, handing analysts a finished investigation and not a queue to work through. The difference shows up in three areas: coverage that does not leave gaps, response that does not require a separate tool, and log management that does not penalize you for ingesting more data. This article walks through how Radiant compares to other AI SOC platforms and legacy SIEM solutions across each of these dimensions. ### Radiant versus other AI SOC platforms Most AI SOC platforms on the market are trained on a fixed set of common alert scenarios. Outside of those scenarios, they have no investigative capability and alerts either go unprocessed or fall back to your analysts. Radiant takes a fundamentally different architectural approach: rather than matching alerts to pre-trained playbooks, AI Research Agents dynamically build and execute investigation logic for every alert type, including novel and unknown threats.

	Other AI SOC Platforms	Radiant
Alert coverage	Limited. Handles only 6-8 common pre-trained scenarios	Complete. Triages 100% of alerts across all connected sources
Novel threats	Requires new training and unable to handle unknown attacks	AI Research Agents investigate every alert like a senior analyst
Centralization	Disjointed tools - separate system for each SOC process	Unified platform for triage, response, and log management
Incident response	Manual response workflows across multiple tools	Unified platform for triage, response and log Integrated: 1-click and fully automated response built into the platform
Pricing model	Usage-based pricing leads to unexpected bills	Predictable and transparent: priced by security use-case
Cost-reduction	Limited cost savings leads to unexpected bills	Up to 85% less on logging costs

### Radiant versus traditional SIEM solutions Legacy SIEMs were designed to collect and correlate logs, not to investigate or respond to threats. They surface alerts through rule-based correlation and pass those alerts to analysts for manual triage. This leaves analysts to handle triage manually at a scale that consistently exceeds team capacity. Volume-based pricing compounds the problem: as environments grow, teams are forced to restrict data ingestion to control costs, creating coverage gaps that would otherwise be closed. The result is a platform that generates alert noise, constrains visibility, and requires additional tooling to complete workflows it was never built to finish.

	Legacy SIEM Solutions	Radiant
Alert triage and investigation	Manual triage workflows with rule-based correlation that requires ongoing tuning	Agentic AI analysts triage 100% of alerts and auto-investigate with full context
Data storage and retention	Pricing forces data sampling and short retention windows	Unlimited retention and full data ownership with cloud-native storage
Incident response	Generates alerts only. Response requires separate tools and manual workflows	Integrated response: 1-click actions or fully automated actions within the platform
Pricing and total cost ownership	Per-GB ingestion fees create unpredictable costs and billing surprises	60–85% logging cost reduction vs. traditional SIEM-based log storage
AI and automation	Static rules require manual updates for new threat patterns	AI agents investigate novel threats without retraining or rule updates
Security outcomes	High false positives and missed threats despite significant investment	Auto-closes false positives and escalates real threats for faster mean to to respond (MTTR)