Sensor data analysis. Without waiting on data scientists.
A self-service engine for analysing time-series equipment data. No data science skills required — sign up, upload your data, get insights.
The same engine that runs Amygda's Platform — for every customer.
Predictive maintenance starts with reading sensor data properly. This is how Amygda does it internally — and now you can run it yourself, no data science team required.
Investigation Projects
Analyse historical data to discover patterns, clusters, and potential root causes behind past asset issues.
Feasibility Studies
Explore whether predictive analytics is viable for your equipment before major investments — or before implementation.
One-Off Analysis
You've got data from new sensors or assets already in hand, and want to know what insight is hiding in it.
It's running in production right now, for every Amygda customer.
Trained and tested on 5TB+ of proprietary data from rail, airport, and aerospace operators — not a public dataset anyone can download.
Build and validate your own models with it, too.
The models running for Amygda's customers today — now yours to build with.
Mapped onto the actual lifecycle of building a predictive maintenance model, from raw data to a prediction.
Prepare
Data Preparation
Upload, merge, transform, and prepare datasets, without needing external tools.
Data Understanding
Checks equipment data for completeness, missing values, and outliers before analysis begins.
Engineer
Feature Trendability
Scores which sensors trend consistently before failures, surfacing early warning signs.
Select
Feature Intelligence
Finds correlated features and recommends the strongest, least redundant set to use.
Model
Equipment State Mapping
Clusters equipment into natural operational states, using all sensors at once.
Change Detection
Flags when equipment behaviour drifts from baseline, using known events or pattern discovery.
Recommendation Engine
Finds historically similar equipment behaviour by matching patterns across time-series signals.
Predict
Prognostics (RUL)
Predicts Remaining Useful Life against sensor thresholds, for single assets or full fleets.
Equipment State Explainability
Explains what defines each state — which sensors and values set it apart.
Prefer to just ask? Query all of this through chat, without touching a notebook — the Data Science Agent.
Built for both ends of the team.
Expert-level analysis, no specialists required
Get expert-level analysis without relying on data scientists. Perfect for investigating specific problems or exploring opportunities in your existing data.
Weeks of work, done in minutes
Accelerate your projects with rapid, comprehensive data analysis. Advanced algorithms deliver insights that would take weeks to develop manually — built specifically for time-series sensor data.