The Future of
is Supervised AI
is Supervised AI
is an Advanced Anomaly Detection engine.
with Supervised Machine Learning.
Supercharged Machine Learning.
By training the model with one-click supervision, Anomify is able to supercharge the machine learning model, reduce false positives and only surface critical events.
It’s a better approach to detection,
saving you time and stress.
Analysing your data 24/7
so you don’t have to.
Fast analysis means fast alerts
straight to your workflow.
Anomify gives you the power to
implement custom algorithms.
Reduce de-bug time.
Get to the root of the
Integrate with your existing dashboards.
Get direct access to our API.
Zero Point of Failure technology
means critical alerts don’t get missed.
Anomify is always analysing.
After ingesting data we learn normal patterns, detect any unusual behaviour, alert on anomalies in real-time, and constantly feed back to improve the model.
Anomify acts on a consensus of cutting edge algorithms to determine all types of anomalies.
Add in, best in class Supervised Machine Learning, Pattern Matching, Correlation and Custom Algorithms, and Anomify has your critical events covered.
From Performance Engineers to the CEO, everyone has a stake in what impacts the organisation.
Anomify empowers teams with fresh data insights, while removing manual threshold and alert fatigue.
With Anomify the whole team gets real-time visibility on events like never before.
Anomify is helping organisations in Energy, Infrastructure, Ecommerce Fintech and more to unlock the power of real-time anomaly detection.
Anomify integrates with your existing data stack to analyse data in real-time, delivering alerts direct to your workflow via Slack, Email, SMS and more so you don’t miss a beat.
Anomaly detection is the process of identifying outliers or unexpected patterns in data.
Machine learning algorithms model the data in order to define a baseline of expected behaviour. Abnormal or unexpected patterns that deviate from this baseline are classified as anomalies.
A time-series is a sequence of data points collected from one source at different points in time and ordered chronologically.
A metric is a piece of data that is tracked to form the time-series. For example, in the energy industry the temperature of a solar panel could be tracked as a metric. In infrastructure I/O from a server could be a metric.
Semi-supervised machine learning is a process for classifying data as normal or anomalous. It involves some human intervention to guide machine learning algorithms.
Unsupervised learning is another machine learning method, requiring no human intervention, but is a poor fit for the anomaly detection problem space because it fails to take account of real-world context and produces more false positives.
Demo: 30-60 minutes
Integration: 1 or 2 days depending on complexity
Learning phase: 10 minutes a day for 30 days supported by our team and documentation
✔️ learn how to better manage alerts
✔️ tune Anomify to interpret normal behavior for your systems.
✔️ spend less time interpreting false positive alerts
✔️ understand your metrics like never before
✔️ have unlocked more time and space in your day
Free trial: if Anomify is not fulfilling your needs at the end of the learning phase is over then you pay nothing.
Simple and fair usage based SaaS pricing.
Contact us for more details.
At our core we are developers.
We built Anomify as we had a need to monitor complex infrastructure at scale. And we’ve done just that.
Over a period of more than two years running on production data, we developed and refined the supervised machine learning method that significantly reduced our alert noise, increasing our focus on the critical events.
Anomify allowed us to quickly detect performance issues across billions of daily events, far beyond what our team could keep an eye on manually.
See how Anomify’s AI makes alerts
better for your organisation.
Self-serve access. No credit card details required.