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Finished Projects

99 %

Happy Clients


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Learn more about Masa's unique features.

A single platform for all sales
channels worldwide

Model Catalog

Explore models built and uploaded by your Data Science team, all from one centralized repository.

Model Management

Manage multivariate models through
A/B testing for live inference and batch

Model Deployment

Create and scale model deployments in just a few clicks. Deploy models developed in any framework or language.

Model Governance

Spend less time on model validation, bias detection, and internal audit processes. Go from model development to internal auditing to production faster than ever.

Model Monitoring

Make better business decisions to save your team time and money. Monitor model performance and detect model decay as it happens.

Model Workflow

Apply business logic to your model prediction results. Create workflows for your models using multiple sources and languages.


Infrastructure Complexity

For companies that don’t have dedicated DevOps teams to help with these infrastructure issues, the responsibility often falls on the data scientists to fend for themselves.

Disparate Technologies

Relying on disparate technologies can be incredibly challenging as they all follow different release cycles, lack institutional support mechanisms, and have varying performance deliverables.

Siloed Tems

By viewing data through separate lenses, collaboration is very difficult, trust in the analytics can be misplaced, and speed of innovation is slowed.

Data Exploration at scale

Exploring data at scale can be difficult and costly.

Model Training is Resource Intensive

Training complex machine learning models against massive data sets can be very challenging in isolation without the ability to collaborate on models with peers.

Difficult To Share Insights

Part of the role of a data scientist is the need to share results with team members and stakeholders for input and decision making. The trick is sharing the insights in a way that resonates with non technical audiences. The inability to do so can hamper cross team collaboration and slow progress.