Data preparation for machine learning

Accuracy and quality

Smartsourcing your data preparation with Keymakr makes sense fiscally and strategically, maximizing your effectiveness and securing data accuracy and quality at the same time.

Targeted annotation

Through cleaning and standardization, contextualized segmentation and targeted annotation, your data is prepared for accurate outcomes.

Data preparation

Data preparation is essential for accurate business intelligence. As such, preparing data is one of the key stages of any business intelligence workflow, but getting high-quality, consistent data is a challenge.

Cost effective

Our cost-effective solutions save you money, maximizing your specialist resources where they are most needed.

Who we are

The team at Keymakr are highly experience data professionals who understand your business needs. With that knowledge, skill and dedication, not only can we provide the highest-quality data for your analysis, but also deliver within your schedules for timely decision making.


Our methods are proven


Human teaching for machine learning

Machine learning has endless possibilities, and it is set to transform how businesses approach their markets. However, machine learning outcomes can only ever be as good as the data it uses, and this is why professional data preparation is so important. Through our careful data preparation, we deliver the information machine learning needs to provide the successful outcomes that your organization needs.

Our methods are proven

The Keymakr team have a track record of success, delivering exceptional results for our partners in a variety of industries and markets. Our expert team produce high quality ground truth data for any market, giving you the raw materials for success.

Smartsourcing

We work with you as a partner rather than a supplier, delivering the data preparation you need within your schedule and specifications. Our service goes beyond outsourcing, but instead is a strategic element of your business analysis that not only saves money, but also allows more effective deployment of your own resources.

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