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by Hubert Deitmers, Managing Partner of Endeit Capital
AI and machine learning can help organisations realise huge efficiency gains and cost savings. But while AI application typically focuses on replacing humans with machines, especially for low value/high volume tasks, Intelligent Empowerment (IE) takes this to the next level.
Companies that achieve IE recognise where these intelligent tools can both complement and augment human capabilities. They fuse the strengths of both to inform better, faster decision-making and free up time for humans to devote to more creative or revenue-generating opportunities.
At Endeit Capital, we expect IE to become more and more crucial over the next five years – those that achieve the right balance will reap the rewards and those that do not will fall behind. I’ve already shared our predictions for IE in the coming decades and details of our partnership with AI.nl, a new platform for innovators to share their insights on digital transformation.
But how do leaders apply this approach in their business model? In this, my third blog, I would like to share some great examples of Endeit portfolio companies that are successfully making the transition.
One of the best examples of Intelligent Empowerment at Endeit is our former portfolio company Hubs (formerly named 3D Hubs). Founded by Bram de Zwart and Brian Garett, the company leverages AI and machine learning to offer a decentralized automated manufacturing platform. It draws on overcapacity in the industrial production market to provide an on-demand service for customers. Hubs doesn’t own any physical machines, instead, it creates value for engineers by providing targeted access to its unique worldwide network of manufacturing partners.
Because the manufacturing market – and especially 3D printing – is rapidly evolving, a ‘one-stop shop’ holds great value for engineers who can save time on outsourcing quotes and finding the parts they need. Using unique machine-learning algorithms and automation, Hubs can instantly provide competitive quotes and design improvement suggestions, selecting the most appropriate manufacturer to fulfill them. Hubs’ algorithms have been instrumental in the creation of many revolutionary products including the fast development of the Kepler satellite and perfecting the production of Fillauer’s prosthetics, both with significant cost savings.
In January 2021, Hubs was acquired by US-based Protolabs to create the world’s largest digital manufacturing platform. Learn more about our investment in Hubs in this blog post by Ilan Goudsmit, investment manager at Endeit Capital.
We recently invested in Amberscript, a transcribing company that is truly embracing Intelligent Empowerment. By combining both machine learning and human capabilities Amberscript obtains 100% accurate text from audio and video in a fraction of the time.
In the transcription industry, there are two broad categories of customer: (i) The mass market, which requires fast (automated) processing and, therefore, accepts some inaccuracies; and (ii) the premium market, which requires 100% accurate text and therefore accepts slower, manual processing.
Amberscript caters for both. AI-driven engines generate 80-90% accurate draft texts. Where this level is not accurate enough (in subtitling for example) humans are then employed to bring the text accuracy to 100%, and they can do this in less than 24 hours.
By harnessing IE, Amberscript can offer a faster, cheaper, and more accurate service than its competitors.
Another great example is our portfolio company Floryn. The Dutch fintech offers SMEs loans of up to €2 million with excellent customer experience management and service. Using machine learning allows the company to make faster and more accurate risk assessments. Instead of assessing dated financial statements, Floryn uses recent and real-time data points, such as banking transactions.
Floryn is driven by technology, data, and processes, making it much more efficient and accurate than any competitor we have seen. Learn more about our investment in Floryn in this blog post by Edwin Hengstmengel, partner at Endeit Capital.
My fourth and final example is Cevinio. This company applies machine learning on human-developed rule-based engines to automate incoming invoice processes for SMEs and multinationals.
Cevinio’s algorithms facilitate the touchless automation of linking invoices to purchase orders. They also run invoice compliance checks and book the invoices into the ledger. This means the time clients spend on invoice processing is two to five times shorter. They also benefit from improved compliance and auditability. Learn more about our investment in Cevinio in this blog post.
Endeit Capital is a founding partner of AI.nl, which discusses the latest developments in Artificial Intelligence.
Endeit refers to the following statement in connection with the sustainable finance disclosure regulation (SFDR), available here.
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