DataProphet, a South African machine learning (ML) startup, has received an investment boost from Knife Capital, according to a statement released by the venture capital company.

DataProphet specifically assists data-heavy businesses, especially in the manufacturing industry, to discover the insights and predictive capabilities hidden in their data.

![Knife Capital DataProphet](/content/images/2018/03/DP2_Knife_DataProphet_Team_Keet_Daniel_Andrea_Frans-min.jpg)
Knife Capital and DataProphet management teams.

“Those that don’t adapt will fall behind, to be replaced and supplanted by newer and more dynamic companies that use machine learning to drive their growt. We are delighted to welcome another credible investment partner like Knife Capital on board to become actively involved in strategic elements of the business and to open up their market access networks in pursuit of growth,” said Frans Cronje, Managing Director and Co-Founder at DataProphet.

Previously, DataProphet had managed to raise investment funding from private investment group Yellowwoods. This time around, although the sums and terms involved have not been disclosed, DataProphet managed to raise what Knife Capital say is a multi-million dollar funding round. The South African venture capital company invests via a consortium of funding partnerships, including KNF Ventures and Draper-Gain Investments.

”DataProphet is a prime example of the kind of cutting edge technologies South African entrepreneurs are capable of developing with global relevance in a fast-growing market. We were impressed with every aspect of the business during our due diligence and subsequent deal closing process, and look forward to the scale-up journey as part of the team” said Andrea Bӧhmert, Investment Partner at Knife Capital.

ML is a vibrant research area under Artificial Intelligence (AI) which helps people and businesses make sense of the data they have. Generally speaking, it is considered a breakthrough in programming because it enables the computer to look for patterns in data and attempt to learn from them. By learning, the computer becomes smarter in the process and is able to sort more patterns effectively. This effectiveness is then applied to real life scenarios.