AI SIEM brings security events together and uses AI to help teams detect threats and investigate what happened. The value is a clearer decision: which activity needs attention and what the evidence supports doing next.
For a business running IBM i alongside cloud identity and endpoint tools, an incident can cross all of them. Our guides connect those practical requirements to the AI Native SIEM and SOC platform we offer.
Choose an AI SIEM platform
Understand the labels and compare the complete buying decision.
AI SIEM terminology: What AI-native and AI-powered actually tell you
Understand the AI SIEM labels before comparing products. Match each claim to the detection and investigation work your team needs.
AI SIEM Tools: What to Compare Before Choosing a Platform
Compare AI SIEM platforms on the investigations your team needs to finish. Check source coverage and evidence before choosing a product.
AI SIEM Pricing: Assets, Data Ingestion, Retention, and Hidden Costs
Compare the full cost of collecting security data and investigating incidents. Include retention and staff time alongside the platform quote.
Protect IBM i and connected business systems
Bring the right records into an investigation that can cross systems.
AI SIEM for IBM i: Connect AS400 evidence to the wider incident
Bring IBM i audit events into the same investigation as identity and endpoint activity. Check collection and field mapping before relying on an AI summary.
AI SIEM use cases: Investigate the activity that puts business systems at risk
Connect suspicious sign-ins to changes on endpoints and business systems. Use these scenarios to decide which AI SIEM workflows your team should test first.
AI SIEM implementation: Get useful investigations from your first data sources
Start with a business risk and the records needed to investigate it. Build a SIEM rollout with tested collection and clear ownership before adding more data.
Run AI SIEM with useful evidence and clear responsibility
Keep history accessible and agree on who can investigate or respond.
AI SIEM data retention: Keep incident evidence useful when you need it
Decide which security records must stay searchable and how to recover older evidence. Compare retention terms against a real investigation before accepting a quote.
AI SIEM governance: Let AI investigate with clear limits on what it can change
Give analysts faster answers while keeping control of sensitive data and response actions. Define evidence checks and permissions before an AI workflow can make changes.
Managed AI SIEM: Know who investigates and who can respond
Match the SIEM service to the work your team needs covered. Agree on monitoring hours and response authority so an urgent case reaches someone who can act.
AI SIEM proof of value: Test the investigation before buying the platform
Compare AI SIEM candidates on your own security questions. Use agreed evidence and acceptance checks to see whether the product reduces investigation work.
AI SIEM questions and definitions
See how our AI Native SIEM fits your environment
Our platform overview covers streaming analytics and behavioral cases alongside AI workflows and long-term retention. Bring the systems you need covered and an investigation you want to improve.
Review the AI Native SIEM and SOC platform or talk with us about your security environment.