The Augos Attribution Engine is a new class of analytics platform. It moves beyond simple visualisation to perform deep causal analysis on high-frequency data, turning your noisy production environment into a clear, AI-ready dataset.
















































You have invested in data infrastructure, but the promised breakthroughs in efficiency remain elusive. This is because factory data is notoriously difficult, and standard BI tools are not equipped to handle its complexity.
Your MES and SCADA systems generate millions of data points, but it is low-frequency, unstructured, and lacks context. It tells you a machine stopped, but not the sequence of events that led to it. Your data lake is becoming a data swamp.
Your dashboards show you that two events happened at the same time, but they cannot prove that one caused the other. You are left to draw conclusions based on correlation, leading to flawed strategies and wasted effort.
Getting clean, structured, high-frequency data from proprietary PLCs and operational technology into your own BI tools or ML models is a huge engineering challenge. This "last mile" problem is the single biggest barrier to true data science in manufacturing.
Your analytical models are only as good as the data you feed them. When they are built on a foundation of manually entered, gamed, or low-resolution data, their predictive power is fundamentally compromised. Garbage in, garbage out.
The Augos Platform is not another dashboard. It is an advanced analytics engine designed to move beyond simple correlation and perform automated root cause analysis on your most complex production challenges.
We bypass your existing low-resolution systems to capture data directly from the machine's control signals. Our engine then processes this complex, high-frequency stream to automatically engineer a rich set of features, such as Inactive Wrench Time or Operator Evaluation Time, that are impossible to see otherwise.
The core of our platform is a causal inference model. The Attribution Engine does not just look for correlations; it builds a dependency graph of every event. It understands that a specific micro-stoppage caused an operator intervention, which in turn caused a call to maintenance.
The output of our engine is a clean, structured, and perfectly time-stamped dataset. It is purpose-built to be consumed by your existing enterprise systems, whether you need to feed a BI tool like Power BI, populate a data lake, or train your own machine learning models.
By understanding the true root causes of performance, the platform moves beyond simply predicting a failure. It can run simulations to prescribe the most effective course of action, showing you that fixing a recurring 10-second jam will have a greater impact than reducing a 30-minute breakdown.
Our advanced analysis is only possible because it is built upon a rock-solid, enterprise-grade OEE data foundation. Our platform masters the fundamentals, giving you the accurate, real-time data you need to power any analytical model.
Live tracking of every planned and unplanned stop.
Real-time monitoring of True Speed vs. Rated Speed.
Automated counting of good units vs. rejects.
The Augos Platform includes a suite of pre-built analytical modules. Unlike standard dashboards that simply visualise raw data, each module is a finished intelligence product, derived directly from our high-frequency, causally-linked data model.
This module provides a defensible financial model of your operations. It moves beyond simple OEE calculations by attributing the true cost of granular events like Inactive Wrench Time or micro-stoppages, sourced directly from our engine. It provides the credible, data-backed financial context that a CFO or board requires.
This is not a simple log of manual reason codes. It is a diagnostic output generated from the machine's high-frequency data stream. It replaces subjective human input with an objective, second-by-second timeline of every stoppage, providing the clean data needed for any serious root cause analysis.
This is a multi-dimensional analysis module, not a simple Pareto chart. It allows your team to pivot and analyse unplanned stops using the rich, engineered features from our engine—such as Technician Response Time or Operator Evaluation Time. It allows you to find root causes that are completely invisible in manually categorised data.
This module statistically analyses the performance of planned events like changeovers and setups. It transforms your SOPs into a statistical benchmark, tracking Time Lost Above Allocated Time and other variances to provide a clear, data-driven path for process optimisation and the standardisation of best practices.
This function generates a structured data object at the conclusion of every shift. It provides a consistent, machine-readable summary of all key metrics, creating the clean, time-series data needed to build reliable models for shift-over-shift performance comparison and trend analysis.
This is your granular event ledger. It provides a complete, exportable, and auditable log that links every job, operator, machine state, and quality event with a precise timestamp. This is the clean, AI-ready source of truth dataset that your data science team can ingest directly into your own models and BI platforms.
The Augos Platform is designed with an API-first philosophy. We do the hard work of collecting, cleaning, and structuring the data so you can get straight to the high-value work of analysis and modelling.
The data you receive is not raw. It has been processed by our engine, cleaned of noise, and enriched with powerful engineered features. This provides a clean, structured, time-series dataset that is perfectly formatted for machine learning applications.
Access the live data stream via a secure REST API. Use our clean JSON objects to feed real-time data into your own applications, build custom alerts, or power live dashboards in other business systems.
Perform bulk data extraction with scheduled exports in standard formats like CSV or Parquet. This makes it simple to ingest large, historical datasets into your data lake or data warehouse (e.g., BigQuery, Redshift, Snowflake) for deep offline analysis or to use in BI tools like Power BI and Tableau.
Our Attribution Engine does not just pass through data; it creates a rich feature set from the raw signal. The metrics below are just a sample of the deep, real-world data our platform engineers to power its analysis.
Stop Spending 80% of Your Time Cleaning Data
Get a clean, structured, AI-ready stream of manufacturing data that you can immediately plug into your models and BI tools to start generating real value.
The "Last Mile" Data Platform You've Been Looking For
Bridge the gap between your operational technology (OT) and your information technology (IT) to finally deliver on the promise of Industry 4.0.
Move Beyond Subjective Reports and Gut-Feel Decisions
Get the deep, causal analysis you need to make truly data-driven improvements, prove their financial impact, and build a culture of operational excellence.
It starts with a quick call with our data specialists to understand your analytical goals and current data architecture.
We will show you the live platform, the structure of the data we provide, and how our engine can diagnose your specific operational issues.
You will receive a clear proposal outlining the solution, data integration path, and transparent pricing.
A personalised demo is the fastest way to see how the Augos Attribution Engine can provide the clean data and deep analysis you need to transform your manufacturing operations.
Stop visualising data. Start understanding it.