AutoCops Netgraph unifies SIEM, XDR, NDR, SOAR, CNAPP, DSPM, CTEM, Vulnerability Management, SAST/DAST, BAS, and phishing simulation onto a single security knowledge graph — so every detection, hunt, and containment is a graph traversal, not a dashboard stitch.
Every incumbent “NextGen SIEM” treats logs, identities, assets, vulnerabilities, code, and cloud posture as separate index domains stitched together with dashboards. Netgraph treats them as a single typed graph where every event, alert, finding, asset, identity, and CVE is a node with edges — and detection, hunting, and containment are graph operations.
L1 triages every alert. L2 investigates with a full entity subgraph. RCA emits a “gap list” of detections that should have fired. The Detection-Drafting agent writes the rule, ships it through the same PR & validation pipeline as a human author, and retroactively replays it across history. The loop closes.
Tiered storage from day one: hot interactive tier · warm columnar archive · cold object storage, all federated by one query layer. Detections live in open standards-based rule languages. If you ever leave, your data is in open columnar formats — you keep querying with any standard reader.
Each module is a full slice — model, repository, API, and frontend page — all reading and writing the same graph. Mate Security competes with none of the broad-stack modules below.
Columnar hot tier · full-text search · OCSF-normalised · multiple rule languages across one fabric.
Five graph-reading agents close every alert with a typed entity subgraph and reasoning trace.
Deep packet inspection · protocol analysis · PCAP retention · identity-aware east-west visibility.
Cloud Detection & Response across AWS, Azure, GCP — identity, control plane, runtime.
IaC scan, drift, admission control, posture — ten pages, all wired to the runtime graph.
CIS benchmarks · custom policy-as-code · discover · classify · monitor sensitive data.
Five stages: scoping · discovery · prioritization · validation · mobilization — reachability-aware.
Prioritized by actual blast radius across runtime + code + identity + data — not CVSS in isolation.
SARIF ingest · Gitleaks · Nuclei · OWASP — findings land on the same graph as runtime alerts.
Coverage map · adversary-emulation test library · CI fails on detection regression.
Templates, schedule, just-in-time training, KPIs — with a native Phish-triage agent.
Natural language → ES|QL / KQL / SPL · notebooks · scheduled hunts on Graph RAG.
Code-first, workflow-orchestrated playbooks — native, not a bolted-on acquisition.
Every new/changed detection auto-replays against 90-day hot/warm and 7-year cold history.
Tamper-resistant artifact vault · hash-chained chain-of-custody · regulator-ready exports.
Statutory clocks for CERT-In 6h, DPDP 72h, GDPR, HIPAA — surfaced on the CISO scorecard.
Two non-negotiables shape every decision we make about Netgraph — from the data model to the default playbooks. They aren't bullet points on a deck; they're filters we apply to every PR.
Designed, engineered, and operated end-to-end inside India. No offshored core, no foreign-controlled data plane, no telemetry leaving the country.
Every module starts from a real SOC pain — an alert that took too long, an investigation that hit a dead end, a regulator clock that almost missed. Not from an analyst report or a competitor's roadmap.
A typed property graph stores every entity. A streaming projector keeps it live from the correlator. Graph-grounded retrieval anchors every agent answer in real edges — no hallucinated entities.
tenant_id is a first-class property on every node.Four stages, one closed loop. Where competing platforms stop at "AI investigates an alert," Netgraph closes the loop — every investigation produces a drafted detection, every detection is BAS-validated, and every change replays against seven years of history before going live.
Unlike AI-SOC overlays that investigate alerts on top of someone else's stack, Netgraph owns the loop: ingest → correlate → reason → act, all on one graph, all on open formats, all auditable, all on-prem if you want.
Across the three dominant categories of incumbent platforms — legacy enterprise SIEM, hyperscaler-bundled XDR, and AI-SOC overlays — each covers a slice. Netgraph covers the stack on one graph, with open data, at SMB-feasible compute.
| Capability | Leading Vendor Type A | Leading Vendor Type B | Leading Vendor Type C | Netgraph |
|---|---|---|---|---|
| Native security knowledge graph | Add-on | No | Yes | Yes — substrate |
| SIEM + XDR + NDR + SOAR unified | Bolted-on | Ecosystem-centric | Overlay only | Yes |
| CNAPP · DSPM · VM native | 3rd-party | Weak | No | Yes |
| Detection-as-Code with BAS gate | Partial | No | No | Yes |
| Open columnar & telemetry formats | Proprietary | Closed log store | Closed | Yes |
| Air-gapped deployment | Limited | No | SaaS-only | Yes |
| DPDP · CERT-In · RBI built-in | Manual | Manual | No | First-class |
| SMB compute footprint (32 vCPU) | No | No | No | Yes |
| Made in India · India-resident operations | No | No | No | Yes |
Vendor types referenced: Type A = legacy enterprise SIEM with bolted-on SOAR (index-heavy, expensive at scale). Type B = hyperscaler-bundled XDR / cloud-native SIEM (strong in-ecosystem, weaker cross-stack). Type C = AI-SOC overlays (deep on triage, narrow on platform breadth). Categories are based on publicly available product documentation and analyst categorisations as of 2026; specific vendor names omitted by design.
Statutory clocks run on the Declared Incidents module — surfaced on the CISO scorecard and exportable as regulator-ready evidence packs with hash-chained chain-of-custody.
Book a 45-minute live demo. We'll wire a sample tenant against your data sources and show the closed loop — alert → investigation → drafted detection → BAS-validated rollout — end-to-end.
Tell us about your stack and what you're trying to consolidate. We'll come back with a tailored demo agenda within one business day.
Drop us a line at hello@autocops.org or use the form — whichever you prefer.