Innovative computer vision startup Neurolabs has attracted $1.2M in funds

Neurolabs is a tech startup with an innovative approach to computer vision which completed a pre-seed fundraising round of $1.2M in the summer of 2020.

The startup is looking to democratize computer vision.

It was founded in 2018 by a technical team of computer scientists and mathematicians who have known each other for more than 10 years, having studied together at the University of Edinburgh: Patric Fulop (CTO), Paul Pop (CEO) and Remus Pop (COO).

Neurolabs founders

An avid learner, Patrick is currently pursuing a PhD in Machine Learning at The University of Edinburgh. He strives to understand the problems he deals with by putting his inquisitive mind to work.

Paul is a passionate data scientist, looking to use the latest Machine learning algorithms to solve real-world problems.

Remus is interested in Bayesian statistics, deep learning and probabilistic modelling. He is also keen to apply these techniques to real-world problems.

Our technology empowers both small and large customers to implement state-of-the-art Computer Vision applications with minimal incremental resources and costs — no coding required, no tedious data labelling, no image gathering.

Neurolabs Investors

Neurolabs received funds from 8 investors. Here they are:

7Percent Ventures which invests only in billion-dollar opportunities

Leading investment firm focusing on early-stage Id4 ventures

The former head of strategy at Microsoft and a prolific investor Charlie Songhurst

Leading investor Techstart Ventures

Deep-tech, seed-stage venture fund Lunar Ventures

Tech angel investor Hampus Jakobsson

Startup accelerators Data Pitch and Fast Track Malmo.

Neurolabs Computer Vision offers Object Recognition as a Service

Neurolabs technology platform allows users to build custom image recognition algorithms using 3D models.

The algorithms developed by Neurolabs interpret and understand the world visually. Using images from cameras, the startup’s Computer Vision models accurately identify and classify objects of interest, helping computers “understand” what they “see”.

Computer vision is not a new technology, it began in the late 1960s, as the subject of a PhD thesis at MIT. It is a branch of artificial intelligence. The technology helps to automate visual understanding from a sequence of images, videos, PDFs, or text images with the help of AI and Machine Learning (ML) algorithms. Learn more about Computer Vision here.

Why is Neurolabs’ approach to Computer vision innovative?

In the traditional Computer Vision approach, you had to take many pictures and manually label them. It was expensive and slow.

What Neurolabs is doing differently is to replace the time and resource-consuming traditional approach with a new approach, one which required minimum resources and costs.

Neurolabs is pioneering the use of synthetically generated data to develop object recognition models in a drastically cheaper and faster way than the traditional approach, pushing the accuracy beyond-human levels.

We deliver Computer Vision-powered Object Recognition to help you automate tasks, boost your business, increase productivity and sales while reducing costs.

The company’s innovative technology leverages 3D models, virtual data generation and deep learning models training.

With Neurolabs’ technology, small and large enterprises can implement state-of-the-art Computer Vision applications with minimal incremental resources and costs.

The Neurolabs Computer Vision platform is universally applicable across industries and scales. The technology allows businesses to automate generic object recognition tasks in industries ranging from hospitality to retail and manufacturing.

Benefits and advantages of Neurolabs’ Object Recognition as a Service:

• No coding
• No image gathering
• No data labelling
• Universally applicable
• Cost-effective
• State-of-the-art accuracy
• Easy to integrate
• Minimal client data
• Automate generic object recognition 20X faster and 100X cheaper

Applications of Neurolabs Computer Vision platform

Grocery retail – autonomous checkout with product recognition

Hospitality – unattended check-out in cafés/bakeries and canteens

Healthcare – utensils inventory, remove human error and prevent foreign object retention post-operation.

Manufacturing – quality control through defect recognition

Robotics – localisation and control

Agriculture – crop grading and sorting

Recycling sorting

Benefits under COVID-19: speed up operations, cut down operational time, reduce time spent in public places, reduce human presence & interaction, ensure a cash-free and safe environment.

Neurolabs is integrated with RPA leader UiPath and blockchain technology rising star Elrond Network.

Neurolabs is a finalist at the annual #UiPathRebootWork and #Automation Awards. Tune in here on the 17th of December to hear CEO Paul Pop explain how RPA developers can leverage the startup’s innovative computer vision platform in a seamless way.

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