Access, Insight, Speed

Access more data.  
Protect data privacy.
Shorten time to value.

Run machine learning on distributed data for faster insights and better outcomes without the cost, concentration risk, long lead times, and privacy concerns of centralizing data.

Insight, Access and SpeedLearn about our approach

Arrive at Better Insight

The efficacy of machine learning algorithms is frequently limited by the accessibility of diverse, quality data sources. By unlocking access to more data and providing transparency of dataset model impacts, you get more effective insight.

Faster Experimentation

Faster Experimentation

The greatest insights often begin with a hypothesis or a question. By accessing data where it lies and rapidly deploying cloud-based infrastructure (where applicable), you’ll lower the costs and time to test data value hypotheses.

Less Engineering Overhead

Less Engineering Overhead

Because Devron offers access to data in situ and removes the need for masking and anonymizing, you won’t need to move data—greatly reducing the overhead of the extraction, transformation, and loading process.

Lower Cyber Risk

Lower Cyber Risk

By duplicating and centralizing data, organizations provide a larger attack surface for bad actors. Devron substantially lowers your cyber risk. Reveal your desired insights without centralizing.

More Data Access

More Data Access

As valuable data arises in more places, it becomes increasingly difficult to access. By federating the algorithm training and preserving the privacy of the data, you’ll quickly unlock access to diverse and valuable data sets.

Preserve Data Privacy

Preserve Data Privacy

From the product roots and current usage by intelligence agencies and privacy-conscious enterprises, data privacy is at the core of our product. Blocking access to the raw, underlying data in distributed data sets, Devron preserves the privacy of data.

Shorter Time to Value

Shorter Time to Value

Obtaining approvals, centralizing data, and building out infrastructure takes time. By using data where it resides while federating and parallelizing the training process, you get trained models and valuable insights faster.

The Devron Platform

Our innovative data science solution leverages federated machine learning to access more of your data where it resides. By increasing the volume of data, you reduce the time to value and increase model generalizability while preserving the privacy of data sources and methods.

Fits Your Data Stack

Devron seamlessly integrates inside your Cloud Data Lakes, Warehouses and Data Processors to enable decentralized machine learning. Our Python SDK provides developer ergonimcs to integrate with all your favorite tools.

Logos of technology companies including: Jupyter, ML Flow, Kubeflow, TensorFlag, snowflake, databricks, PyTorch and scikit Learn
A Jupyter notebook with data statistics
stats_result.profiles[satellites[0]]

If you’re familiar with Jupyter notebooks, you’re going to feel right at home with Devron. Use our APIs to pull remote data into an environment for rapid discovery.

Our Partners

See how Devron can provide better insight for your organization

Request a Demo