Control Plane

• API Gateway & AuthN/Z: OIDC/SAML (e.g., Keycloak), multi-tenant RBAC/ABAC, quotas/rate-limit.     
• Agent Orchestrator: planner → tools → critic → memory loop; adapters (MCP/tooling) for Splunk, PAN-OS, CrowdStrike, etc.; policy guardrails (PII, change windows, approval checks).    
•  Playbook Engine (SOAR): visual runbooks, tests/versioning, human-in-the-loop gates, rollback. 

Detection, Reasoning & Enrichment 

• Stream Processing & Rules: Sigma/YARA-L, correlation & dedupe, UEBA/behavioral models.    
• LLM Services: triage summaries, root-cause hypotheses, natural-language to actionable tool queries.     
• Enrichment: asset/identity context (CMDB/IdP), STIX/TAXII intel, Geo/IP/DNS/WHOIS.     
• Knowledge & Vector Search: SOPs/runbooks/case KB + embeddings (RAG), entity/attack graph. 

Storage & Indexes  

• Hot search: OpenSearch/Elasticsearch for notables, cases, artifacts.     
• Data lake: Parquet on S3/MinIO for long-term retention.     
• Relational (OLTP): PostgreSQL for cases, users, RBAC, configs.     
• Vector/Graph: pgvector/OpenSearch kNN + entity/relationship graph. 

Integrations (on the right side of the diagram)   

• Ingest:     
• Splunk SIEM via HEC/Saved Searches/REST.     
• Palo Alto PAN-OS via Syslog + XML/REST.     
• CrowdStrike Falcon via Streaming API/REST.     
• Others: Email, Proxy/DLP, DNS, NAC, EDRs, Cloud logs.     
• Normalize to ECS/UDM; batch 

S3/CSV/Parquet drops; quality checks & PII redaction.   

• Actuation:     
• PAN-OS: push rule/block IP/hash.     
• EDR: isolate/kil l process.     
• Splunk: update notable status/comment.     
• ITSM (ServiceNow/Jira): auto-ticket & enrich.     
• IdP (Okta/AD/M365): disable/force reset. 

Platform & Ops (on-prem / air-gapped ready)  

• Kubernetes/OpenShift (operators/Helm), HPA, service mesh.     
• Secrets & supply chain: Vault/KMS, private registry mirror, air-gap updater.     
• Observability: logs/metrics/traces, SLOs, health checks, alerting.     
• Security & governance: network policies, CIS hardening, immutable/auditable trails. 

Typical alert-to-action flow (agentic)   

1. Ingest alert from Splunk or syslog (PAN-OS) → normalized → quality checks.     
2. Detect/Correlate with rules + UEBA; dedupe & group into incidents.     
3. Reason: LLM summarizes, proposes hypotheses & next best actions; planner picks tools.     
4. Enrich: pull context (asset, identity, TI feeds), fetch raw evidence (Splunk query tool).     
5. Decide: orchestrator evaluates policy guardrails; if sensitive, request analyst approval.     
6. Act: run playbook steps (e.g., PAN-OS block, EDR isolate, create ITSM ticket).     
7. Document: case updated with evidence, actions, approvals; KPIs/dashboards refreshed.  

Deployment notes (on-prem realities)   

• Air-gap: mirror container registry; offline model/KB updates; deterministic build pipeline.     
• Data residency: S3-compatible storage (MinIO) with lifecycle policies; per-tenant encryption keys.     
• Scale: split hot/warm/cold tiers; queue (Kafka/RabbitMQ) between ingest and processors; shard OpenSearch.     
• Models: serve locally (e.g., vLLM/NVIDIA Triton) with policy-filtered prompts and response audits.