Ready-to-go, comprehensive, automated anomaly detection

You are seeking to find never-before-seen anomalies in metrics data without specifically labeling normal or specifying thresholds. Need to do this without any data science training and not be limited to certain system or process.

Try with your data Docs ->

Analyze complex patterns

Discover and recognize anomalies and critical patterns from multivariate data

Control analysis costs at scale

Process and analyze terabytes of batch and real-time data from many sources

Make engineers more productive

Extract findings and enable mission-critical operations without programming skills

Why use Time Series Intelligence to spot anomalies?

Find earlier indication of trouble without increasing effort to respond to anomalies. Eliminate expert effort to set up or maintain anomaly detection. Find new incidents without previous examples. Reduce computation required to deeply analyze time series data

Difficulty to label normal

High noise levels in data

Concurrent anomaly causes

Tens of thousands of signals

Changing baseline operations

Limited compute resources

PatternIQ™ drives automated anomaly detection

PatternIQ™, Falkonry's patented technology, is key to the scale and efficiency of time series intelligence. It provides advanced data-clock-based task scheduling and convolutional variational autoencoder for multi-timescale embeddings reflecting shapes, waveforms and value distributions.

Collect and organize data from multiple sources

Time Series Intelligence enables you to bring together data from multiple sources, including MQTT, OTel, S3, and more so you can analyze across sources.

Connect to cloud data sources natively
Supports numeric and categorical data
No need to resample or compress data
Organize data into multiple hierarchies for easy selection

Learn more ->

Dynamic charts of time series data

PatternIQ™ provides native tools to visualize high resolution data in a fluid and responsive display while navigating through your own system hierarchy.

Zoom out to months of 100 Hz data
Visually spot anomalies in data
Display as time plots, distributions, buckets and heatmaps
Accurately view data at any scale and resolution
Exploit metadata to rapidly select only the right metrics

Apply domain rules and conditions

Translate time series into discrete events and alerts based on expert knowhow and operating constraints.

Efficiently apply a rule across metrics
Translate AI inferences into actionable insights
Evaluate windowed criteria without coding
Reduce alert frequency through debouncing strategies
Drive automation and integration with workflow systems

Helpful Resources

Technical Paper

Prioritized Anomaly Management in Steel Production Using Self-Supervised AI

Webinar

How SCAE improves physical maintenance despite limited factory resources using AI-powered guidance

Blog post

Quantifying the Impact of Anomaly Detection

AISTech

Automated, Scalable AI for Real-Time Monitoring of Steel Continuous Casting System

Take control of your mission.

Take away drudgery and toil from exploiting real-time data from sensors and telemetry. Rapidly figure out what's going on.

Start a trial