Using data ethics for competitive edge

Making Data Ethics Your Competitive Edge

The hottest job in data science could soon be a philosopher who guides data science practitioners in the murky field of data ethics.  Simply put, data ethics is a sub-field of ethics which defines a set of rules that state what is moral behaviour. Moral behaviour in data science is not simply an academic exercise…

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AI driven competitive intelligence

AI-driven Competitive Intelligence

These days businesses have great visibility internally, into their sales, marketing, product metrics and strategies, but lack visibility externally. To outdo competition businesses should implement Competitive Intelligence services that convert data into intelligence that can provide a real-time view of your competitive landscape. We’ve found great value in machine algorithms that can help identify trends…

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are you ready for AI?

Are you ready for AI? Launching an AI project: first steps checklist

In over 2,000 enterprises surveyed, 47% of these have already launched or are already using AI in their organisations. A lot of businesses are on the way to becoming empowered by AI, however, there are still a lot of businesses out there that struggle to understand AI, its value and what it takes to build.…

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How to manage an AI project

From Proof of Value to Production: How to manage your AI projects

“Every company is a technology company.” Gartner This quote from Gartner represents businesses increasingly adopting sophisticated technologies to achieve their goals. Artificial Intelligence is one of the most important business opportunities in 2019. Knowing what it takes to apply these new technologies to work at scale and give a greater competitive edge, is the real…

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Starting an AI project

2 things to consider before starting an AI project

Clients often contact us with questions and are curious to know about what AI can do in their organisations. However, they are often caught by headlines about AI changing this or that industry, hung up on the idea that AI will solve all their problems. Therefore, they jump on starting an AI project right away.…

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Skim Engine Updates: Address Extraction

Skim Engine Updates: Address Extraction

Updates with our customers in mind The main advantage of our address model is its ability to accurately detect and extract addresses from any web page.With this new feature of the Skim Engine we are trying to provide solutions to the absence of address detection model in either open source or commercial form. Technical approach…

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Explainable AI

Bleeding Edge Series: Explainable AI is the key to Social Acceptance of Artificial Intelligence

Why do we need Explainable AI? Systems that rely upon artificial intelligence to make decisions are often black boxes that produce values which are interpreted to signify a certain meaning. There is often no explanation of how the system arrived at these values. This lack of explanation may not be an issue for problems such…

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BECCA’s Recommendation Engine

From research to care, Breast Cancer Care and Breast Cancer Now put people affected by breast cancer at its heart providing support for today and hope for the future. United, the charity has the ability to carry out even more world-class research, provide even more life-changing support and campaign even more effectively for better services…

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Skim Engine Updates: Address Extraction

Skim Engine Updates: Geo Tagging

The Skim Team have been working on new features for our Skim Engine. The first of which was announced at the beginning of the week relating to Entity Extraction. For this feature our team focused on Geo Tagging. The Skim Engine will be able to extract any geographical locations – villages, countries, cities, oceans, rivers,…

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Skim Engine Updates: Address Extraction

Skim Engine Updates: Entity Extraction

We’ve been working on upgrading and improving our Skim Engine, expanding its already existing capabilities for data extraction. Generally, the Skim Engine is able to transform unstructured data into structured and machine-readable data. The available data is used for standard processing that can be applied for retrieving information. For this particular feature of entity extraction,…

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AI for Supply Chain

Increase visibility with AI for Supply Chain

According to the McKinsey global survey; Supply Chain is one of the top areas where businesses are gaining greater revenue from Artificial Intelligence and technology investments. 76% of the respondents reported moderate to significant value from deploying AI in their organisations. In fact, AI for supply chains hold high potential for boosting both top-line and…

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Machine Learning for Churn Prediction

4 Reasons To Use Machine Learning For Churn Prediction

In this blog, one of our Data Experts Marcia Oliveira explains 4 reasons why Machine Learning for Churn Prediction is more efficient than traditional methods. No business is immune to the risk of losing customers, but is there more you could be doing to retain them? A monthly customer churn as low as 5% doesn’t…

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how to tun a data science team

How to run a Data Science Team: TDSP and CRISP Methodologies

In this blog, we are introducing two well-known Data Science methodologies for project management, namely, CRISP-DM (Cross-Industry Standard Process for Data Mining) and Microsoft TDSP (Team Data Science Process). Here at Skim Technologies, we adopted TDSP as a guiding Data Science methodology to help us build great products for our clients as it places more…

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Scale-ups outsource data science

Why Scale-ups Should Outsource Data Science

UK & US Data Scientists demand vs supply Data Scientists demand is fueled by the increasing commercial adoption of Machine Learning and AI-powered solutions. In an article, Raconteur quotes a recent report from Accenture, forecasting that “AI will add £654 billion to the UK economy by 2035. A significant portion of that will be outsourced…

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Bleeding Edge Series: Automatic Machine Learning

By Marcia Oliveira 20 minutes read In this article, we look to dispel the myth that AutoML is replacing Data Scientists jobs by highlighting three factors in Data Science development that AutoML can’t solve, and why. 3 Reasons Why AutoML Won’t Replace Data Scientists Yet. Automatic Machine Learning (or, simply, AutoML) is a field that…

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Our mission

Skim’s mission is to empower people to use data more effectively and to demystify artificial intelligence. Rather than holding up the common narrative of machines replacing humans, we see how machines can help humans to have easier lives and better businesses.

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London EC2M 5NT

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