Alert management, AI analysis, threat intelligence, investigation, and automated response in one cohesive platform. No tool sprawl, no swivel-chair between consoles, no context lost between handoffs.
A deterministic Evidence Intelligence Layer computes correlation, telemetry, campaign, and business-impact signals before any model runs. The AI only reads that evidence to explain a verdict, so every call is reproducible and auditable, not a black-box guess.
Run the full platform and its AI inside your perimeter, air-gap capable, or as a managed multi-tenant cloud deployment. Your data, your infrastructure, your rules, either way.
Rules, deduplication, and known false-positive patterns resolve the noisy majority without any inference.
resolved · no LLMCorrelation, telemetry, campaign clustering, and business-impact signals computed deterministically, then fused with threat intel.
evidence · deterministicSix specialized workers read the evidence, on-premise or in the cloud: threat, intent, impact, false-positive, and MITRE ATT&CK mapping.
reasoned · mappedAuto-close FPs, escalate criticals, and trigger containment, each verdict backed by the evidence it was built on.
verdict · actionInstead of one opaque model call, SOCNova runs a Reasoning Orchestrator: six specialized workers each read the same deterministic evidence and reason about one dimension of the case. A synthesizer fans their outputs into a single, contradiction-checked verdict your analysts and auditors can follow.
SOCNova runs a purpose-built cybersecurity LLM as its analysis engine. Deploy it fully on-premise, air-gap capable with zero external calls, or as a managed cloud service. Either way, no bytes of analysis are sent to third-party AI providers. GPU-accelerated inference returns a median verdict in under four seconds, and the model reasons only over the evidence the pipeline has already computed.
Before any model runs, the Evidence Intelligence Layer computes a structured evidence bundle for every alert using rules, not inference: correlation signals, telemetry derivations, campaign clustering, and business impact. Same input, same evidence, every time, so results are reproducible and auditable. The LLM never invents facts; it only explains the evidence EIL already produced.
A proprietary composite that fuses technical severity, exploit probability, weaponization status, intelligence signals, and recency into a single 0 to 100 score, so your team knows exactly which threats demand attention now.
The SOCNova AI engine evaluates severity, assigns risk, and reasons about every alert that reaches it, on-premise or in the cloud, with no third-party data egress.
A deterministic pipeline builds correlation, telemetry, campaign, and business-impact evidence for every alert before any model runs, so verdicts are reproducible and auditable.
Six specialized workers each reason over one dimension of the case, then a guarded synthesizer fans their outputs into a single, contradiction-checked verdict.
44K+ IOCs across 12+ curated feeds, plus USOM and local intelligence, fused into the ATS composite threat score.
Recurring false-positive patterns are detected automatically and turned into tuning suggestions, so the same benign noise stops reaching your analysts.
SOCNova proposes ready-to-deploy SIEM and EDR detection rules from analyzed activity, closing coverage gaps without hand-writing every query.
Auto-close false positives, escalate criticals, and trigger host isolation or IP blocks through your existing EDR and firewall connectors.
Build cases from correlated alerts, walk the attack graph, and bridge alerts to investigations without leaving the workflow.
Every analyzed alert is mapped to relevant techniques and tactics with traceable provenance, exposing adversary behavior and defensive coverage gaps.
Executive summaries, incident reports, and compliance documentation generated from analyzed data, stakeholder-ready in one click.
Five-role access control, scoped permissions, and an append-only audit of who did what and when, across the whole platform.
A conversational copilot for analysts: IOC lookups, MITRE explanations, and containment guidance in natural language.
Every security-relevant action is written to an append-only log protected by an HMAC hash-chain. Records cannot be silently altered or deleted, and the chain can be cryptographically verified on demand.
APPEND-ONLY · HASH-CHAINEDKVKK-aligned data handling and audit-integrity controls suited to finance, banking, energy, public sector, and other regulated environments. IOC lookups are redaction-aware so sensitive identifiers stay protected in the trail.
KVKK · DATA RESIDENCYEmail-based two-factor authentication with Redis-backed sessions, Ed25519-signed hardware-fingerprinted licensing for offline deployments, and five-role RBAC governing every action.
ED25519 · 5-ROLE RBACA multi-layer defense screens model inputs against injection and manipulation, because an AI SOC that can be talked out of a verdict is not a control at all.
MULTI-LAYER · HARDENEDServices bind to localhost behind an nginx TLS proxy, with host firewalling and brute-force protection in front. Databases and the model runtime carry no externally exposed ports, and each service is isolated in its own container.
FIREWALLED · ISOLATEDA layered backup system covers data and the signed model artifacts, so a full environment, inference engine included, can be restored from verified backups after any failure.
VERIFIED · RECOVERABLEThe full platform and its cybersecurity AI inside your perimeter, air-gap capable, zero external dependencies, complete control of data and model.
A multi-tenant managed deployment with database-layer isolation per tenant, enterprise depth without the infrastructure lift, scaling with your alert volume.
The honest way to evaluate SOCNova is against your real environment. Tell us about your stack and our team will scope a demo to it.