Outsourced
machine learning

that simply works.

Your complete machine learning operations ecosystem.

Bsogood empowers organisations who do not have the people, resources, time, or knowledge to implement and scale machine learning within the business. Removing the requirement of costly machine learning specialists, data scientists, software developers, and operations teams. The unique architecture within our product eliminates expensive cloud and bandwidth requirements. Accelerating the deployment and management of robust and scalable machine learning models within your business.

How we benefit your business

Our cutting edge architecture is built around inference at source, reducing cloud costs, complexity, bandwidth, and risk to businesses. Coupled with our rule defining service offering, we offer high value to businesses seeking to implement, or enhance their machine learning capabilities.

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  • Understand the data in your business, learn how machine learning can increase efficiency and reduce cost.
  • Deploy and monitor complex machine learning models, correctly, at cost-effective speed.
  • Remove the need for specialist, highly skilled resources within your business.
  • Save time and money by reducing overheads and increasing flexibility to scale.
  • Mitigate risk, focus on what your business does best.

The status quo in technology is broken.

Tired of dealing with technology partners and agencies that promise the world in a sales pitch and don't deliver?

The tradition within technology has been big promises and poor results. This is a result of stale structures, tired engagement models, and a disconnect between sales and how things should be done.

We believe in a new world, one where great technology is communicated and implemented correctly from the start. We have torn down the construct of "normal", and rebuilt our service around what works.

Get to know machine learning, understand your data, and start making informed business decisions that lead to efficiency and cost savings.

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What our customers have to say.

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