Industry: Cloud Operations | DevOps | SRE

Causely: Intelligent Anomaly Detection for Cloud Operations

2000x Faster Inference | Zero-Shot Deployment | No Training Required

Causely monitors cloud service latency and other telemetry signals to detect anomalous events in real time.

The Challenge

Causely’s existing anomaly detection system relied on NeuralProphet with confidence interval-based thresholding to identify anomalous latency patterns in cloud services.

The Solution

Simulacrum deployed its LAFN foundation model to revolutionize Causely’s threshold determination process.

The Impact

The probabilistic approach provides tighter, more reliable thresholds by working directly with distribution quantiles rather than point forecast intervals. This enables Causely to distinguish genuine service degradation from normal variance with greater precision.

Why Simulacrum?

Foundation Model Advantage: Our LAFN model is pre-trained on diverse time series data, enabling zero-shot deployment without client data training.

Probabilistic Forecasting: Full probability distributions provide richer insights than point forecasts, enabling better decision-making under uncertainty.

Enterprise-Ready: Sub-second inference, API-first architecture, and hands-on support for seamless integration.

Domain Agnostic: From cloud operations to construction, our technology adapts to your industry's unique patterns.