CausalOps

Know Why,
Not Just What

Causal inference replaces correlation-based monitoring. Discover the actual root cause of network issues — not just symptoms that look similar.

The Problem

Correlation ≠ Causation

73%

of alerts are false positives in correlation-based systems

4.2 hrs

average MTTR when engineers chase correlated symptoms instead of root causes

$5.6M

average annual cost of network downtime per enterprise

Causal Discovery

From Telemetry to Root Cause

Firmware UpdateTraffic SurgeBGP FlapCPU OverloadRoute ConvergencePacket LossLatency SpikeRoot CauseIntermediateEffect

Insight: The causal graph reveals that the firmware update was the true root cause of the latency spike — not the CPU overload that appeared simultaneously.

Architecture

Three Pillars of Causal Intelligence

Causal Discovery

from Cortex

DoWhy-powered causal graph generation from VPC flow logs, SNMP traps, syslog, and OTel telemetry. Automatically discovers causal relationships that correlation analysis misses.

Intelligent RCA

from Lighthouse

AI-driven root cause analysis that follows causal chains, not correlation clusters. Reduces MTTR from hours to minutes by eliminating false leads.

Network Digital Twin

from Meridian

Graph-based topology reasoning with simulation-validated remediation. Test fixes in a digital twin before deploying to production.

Causal Estimation

Quantify Impact Causally

Causal Impact Analysis

Effect of Router Firmware v3.2.1 Update on End-to-End Latency

45ms
Before
12ms
After
Average Treatment Effect:-33ms(p < 0.001)

Confounders controlled: traffic volume, time of day, peer congestion

API

Developer-First Interface

MethodEndpoint
POST/v1/causalops/discover
POST/v1/causalops/ate
POST/v1/causalops/counterfactual
GET/v1/causalops/graph/{id}
POST/v1/causalops/rca
GET/v1/causalops/topology
Get Started

Ready to Move Beyond Correlation?

Request Institutional Briefing