In this blog post, we explore how we boost our MLaaS approach to create the best blend of innate human nuance and computational ability of machines to solve your business challenges…

How Calligo uses machine learning as a service (MLaaS)

Machine learning as a service (MLaaS) is machine learning (ML) technology offered by a cloud-based company that you can use to avoid having to build in-house ML solutions. It’s a similar concept to SaaS (software as a service) or PaaS (platform as a service).

MLaaS means you can get instant access to incredibly powerful tools and solutions without needing to invest the time, money and resources to build the solutions yourself.

However, MLaaS isn’t something you buy and it fixes everything. It needs support. Some places advertise instant results but there always needs to be an aspect of customization and optimization. Businesses face similar challenges but their specific situations are unique.

At Calligo, we don’t just hand over our MLaaS solutions and leave you to implement them. We use optimized tools paired with data scientists and our experience to balance the best blend of innate human nuance and computational ability of machines to solve your business challenges. This helps make sure you’re getting the most value out of a MLaaS approach which will deliver the best ROI.

In practice, MLaaS delivers real-world results such as saving a global manufacturer millions in repair costs and improved product quality with machine learning.

How Calligo can transform your data with MLaaS

Our MLaaS approach provides fast and easy deployment that seamlessly integrates into an ongoing ML-focused monitoring system. Our MLaaS approach (for development, we call this solution acceleration) optimizes the production of solutions by up to 80%, without compromising customization or model value.

This is how we do it:

  • A Calligo expert will work with you to determine what use cases are meaningful and worth developing.
  • We work with you to build solutions using technology that optimizes the balance between human intelligence and computer automation (not relying completely on either).
  • We review results and how well they can be integrated into the business. Many solutions out there hyper-focus on accuracy, but chasing accuracy doesn’t automatically mean it’s a good solution which gives real-world returns.
  • We deploy models and continuously monitor model behavior to ensure continued return on the investment. We make sure the model is staying relevant to the changing business and it continues to ‘learn’ as expected.

When to use Calligo’s MLaaS approach

You can make use of Calligo’s MLaaS approach at any stage in your business cycle. Our MLaaS approach works particularly well if:

  • your data scientists are stuck in the weeds working on aspects that could be automatable and you need their time to be freed up to work on wider things like strategy, or stakeholder management.
  • you’ve got a small in-house team with less ML expertise. Using MLaaS helps augment the team’s knowledge and capacity to deploy machine learning.
  • some or many of your use-cases could be outsourced to a predictive API.
    your company produces a lot of data and you need to carry out regular tests on the data, or interrogate it regularly to be able to pivot your offering.
  • you run a microservice-based architecture, you could use Calligo’s MLaaS approach to properly manage microservice architecture.

What are the benefits of machine learning as a service (MLaaS)?

Experts navigating the perfect balance of human and machine

You’ll immediately get access to specialized experts in Calligo who will be able to guide you and shape the offering to exactly meet your needs instead of having to recruit and retain this knowledge in-house.

What’s more, at Calligo, we specialize in understanding the untapped potential of how humans and machines can work together to deliver the best ML solutions. We have insight and experience for which aspects of a data strategy can be automated by machines and which aspects need human intervention, for example, wider strategy or stakeholder management.

Saves your company time and money

By avoiding having to conceptualize, build and maintain your own in-house machine learning solution, you and your data scientists can save time and money and divert the resources to meaningfully growing other aspects of your company.

Deploy market-leading technology

With MLaaS, you instantly have access to market-leading technology which a company like Calligo would work with you to customize, deploy and optimize to fix your exact problems. Your road to success would be exponentially sped up.

Increased productivity and delivery time

The 2020 Algorithmia survey shows over half of enterprises need 8 – 90 days to deploy one model. What’s more, 18% of teams spend 90+ days productionizing a single model. When you weigh that up for the opportunity cost of what the team could have been working on instead, the days begin mounting up.

The machine learning infrastructure can be pre-provisioned and configured at a rapid pace so your team can work faster to realize faster results and delivery can increase.

There’s no arguing that MLaaS is an incredibly powerful tool that’s already being wielded across all industries and sectors.

Get in touch with Calligo’s expert team to discover how you can use our MLaaS approach to augment your team’s knowledge and improve your company’s results using machine learning as soon as tomorrow. What are you waiting for? Fast-track your success today.