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What Can Watchful Do For You?

The Problems We Solve

Implementing Machine Learning in the enterprise is a resource and time intensive task. In an ever-changing environment modern data-driven organizations need to be able to develop, implement, and monitor machine learning models that perform in production. One of the biggest roadblocks to building effective models is the need for large amounts of labeled training data. This can prevent ML solutions being implemented in parts of the business where there is clear value, but were not implemented due to data challenges. Watchful solves this problem by providing organizations with the tools necessary to build ML solutions that are easy to maintain, monitor, and improve through the ability to turn raw data into large amounts of high-accuracy training data quickly and programmatically. This enables businesses to respond quickly to rapidly implement new solutions by making data scientists 10-100x more efficient through cutting edge machine learning and statistical techniques to distill, scale, and inject domain expertise into their models.

Who Benefits?

1. CIO/CISO - Accelerate organizational ML maturity by tackling the first step in any ML pipeline, the data and data labels. Further automate and increase performance of existing ML pipelines by implementing Watchful. Keep agile to changing environments by being able to rapidly implement new ML solutions. Tackle use cases that you never thought were possible because you couldn’t acquire the data.

2. Data Scientists - Rapidly iterate on new ideas and simply push better models at a faster rate. Quickly build a business case or prototype for a new idea in a matter of hours without labeling data or needing to acquire it. Remove roadblocks due to constraints on labeler’s bandwidth or organizational resources by being able to independently generate your own training sets.

3. ML Managers/Leaders - Finish more projects in less time by spending drastically less effort and energy in data acquisition, exploration, and labeling. Increase productivity of your Data Scientists and improve the performance of existing models by simply augmenting existing training sets with large amounts of Watchful-generated labels.

Key Benefits

Stay Agile

Keep agile to changing environments by being able to rapidly implement new ML solutions or augment your existing ones. Implementing models in an ever-changing (and even adversarial) environment is a daunting task. With Watchful, implementing changes to your models in minutes or hours can save organizations massive amounts of time, effort, and energy.

Productivity + Performance:

Supercharge your data scientist’s productivity. Accelerate organizational ML maturity by adding further automation to existing pipelines while also increasing performance with programmatic, probabilistic labels

Bring ML to more of the business:

Tackle projects and problems that were considered too difficult or expensive due to some combination of the lack of subject matter expertise or the cost to acquire appropriate data sets.

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