The Tagup Platform

Unify Asset Data. Predict Failure.

Secure. Scalable. Available 24/7. The Tagup Platform provides you with an unprecedented 360o view of your equipment data. Maintenance records, reference documents, nameplate data, and real-time sensor measurements are consolidated into a unified asset record.

This data powers the Tagup analytic models, accurately predicting equipment failure.

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Eliminate data silos

Unlock your equipment data’s potential. By combining all varieties of equipment data into a common schema, the Tagup platform makes it easy to train machine learning models. Data is accessible to authorized users via RESTful API, enabling your internal teams to build and deploy analytical models in a snap.

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Predict the future

Based on our team’s research at MIT, our platform’s algorithms tell you when your machines will fail. No more deterministic rules, threshold alarms, or waiting for an asset to fail. Our models consider all asset data available, become smarter as more data is collected, and identify issues well before they cause business interruption.

Making it happen

01 Data consolidated from disparate sources
02 Data is cleaned and mapped to platform schema
03 Models trained and validated against asset data
04 Best performing models and all asset data available via application and API

Our unique value

Everyone is talking about predictive analytics. What’s different? Existing solutions can’t reliably estimate time to event, they only identify if something is amiss. We see a unique opportunity to enhance asset inspection, maintenance, and procurement decisions.

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1

A new approach to failure modeling.

Using patent-pending and continually evolving survival models, the Tagup platform verifiably estimates the time until a failure event or required maintenance action.

2

A deep focus on specific equipment types,

with some of the world’s largest operating and failure data sets in multiple equipment categories. We are selective in incorporating new asset types into the platform. By building the largest data sets in specific applications, we are able to train the deliver the most accurate models.