Build. Deploy. Run.

Speed up your data processes from development to production with Dataploy, a cloud DataOps platform.

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01

Build

Easy configuration on a serverless platform

Python and R Compatibility

Dataploy helps you being more flexible and efficient. You can build your data process in your preferred language.

Cloud-based, Worry-free

Save time and money with our serverless solution. You won’t have to worry about maintaining and stopping your own servers. With Dataploy you just pay just for the time you need.

Git Integration

Automatically checks out your code from your git repository

02

Deploy.

Time-saving and error-free automatic deployments

Continuous Integration

Run tests and automatically deploy if they passed or be notified if they didn't

Model Quality

Define your minimum model metrics (e.g. accuracy) and check their evolution

Model Versioning

Monitor your key models metrics and analyse its evolution over time

03

Run.

Be ready for scale and monitor your performance

Serverless

Run the predictions and download reports with a simple API request

Monitor

Check for use and performance metrics.

Scalable

Automatically scales up when needed.

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Use Cases

Banking

Model Performance Monitoring

In banking, decisions supported by predictive models have a direct economic impact on the company. That's why it's critical to monitor model performance metrics. Dataploy includes a monitoring system that allows controlling metrics and setting alarms in case of performance drop.

Fraud Detection

A fraud detection system must be able to detect non authorised transactions immediately to minimise economic loss. Dataploy allows to deploy your fraud detection model in a scalable system, so it will be always available.

Model Evolution

Data models have to be efficiently evolved when new regulations appeared or more data is available over the system. With Dataploy, data scientists are able to change the models to add new variables or restrictions, and the platform will automatically run tests and deploy the changes. Also, Dataploy allows data scientists to schedule periodic retrains on new data easily.

IoT

High Scalaibility

Internet of Things projects are being deployed over complex installations to gather and process big amounts of data. In those scenarios, it's critical to have a highly scalable system, so it will be cheap when there are few sensors and powerful on a bigger infrastructure.

Industry

Constant data retraining

Predictive maintenance models are being implemented in many industry companies, so they can reduce repairment costs. Machinery faults are rare, so this models have to be constantly retrain with new data to be effective. Dataploy allows to schedule this retrainings periodically with an easy configuration.

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