Fast and scalable pipeline to enable AI with big data

Reference number
Coordinator Asymptotic AB
Funding from Vinnova SEK 300 000
Project duration November 2019 - March 2020
Status Completed
Venture Innovative Startups
Call Innovative Startups step 1 autumn 2019

Purpose and goal

Innovative research and development plays a crucial role in the area of Artificial Intelligence (AI). With this Vinnova funding, the goal was to achieve both technical advances for our AI platform and to expand our marketing and network. Technically, we have implemented two key components using the state-of-the-art deep learning technology. As a result of market exploration and networking, we have established several strategic partnerships and we are now in contact with multiple potential customers.

Expected results and effects

This Vinnova funding has helped speed up our development significantly. With this resource, we spent about 500 hours on marketing, research and development. We have built an automated deep learning system as part of our AI platform and delivered partial results as a demo to our potential customers. We have expanded our market and network with this funding and hence increased our visibility. As a result of the technical demos and the marketing effort, we have established multiple strategic partners and potential customers.

Planned approach and implementation

The implementation consists of four phases that have been accomplished in this project: 1. Expand the technical capacity of our AI platform to handle new types of data from potential customers; 2. Implement a prototype of a highly automated deep learning module and its quality control as part of the AI platform; 3. Explore the market by collecting requirements and feedback from potential customers; 4. Given the requirements, adjust and deliver the output of the developed system as a demo deliverable to our potential customers and iterate upon further feedback.

External links

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 1 May 2020

Reference number 2019-04115

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