Appen had a conference call regarding their latest update. They got really defensive on revenue growth etc... Especially when it came to how their top 5 customers (Comprising 88% of revenue) have reprioritised their data-intensive projects to other projects concerning vertical integration. They believe it is a "near-term" headwind and those customers will continue with previous projects after Covid.
Their growth plans with the government took a massive hit (pandemic of course) and halted the sales growth there. They are very optimistic about autonomous driving technology and are labelling data on test cars across race tracks.
The market belted the company on reducing the guidance estimates. However, the market is not looking at the longer-term picture with autonomous driving. Tesla will lead and vertically integrate but other car companies will use third party tech for their autonomous vehicle. Appen can be part of the third party tech. Comma Ai is used extensively across GM fleet, as well as Luminar for Volkswagen. Appen should sign up deals with companies like Comma Ai who have the data so that they can label the training data as Comma Ai does not have a large workforce.
I do not know how far away they are with customers in the self-driving space and that was going to be my question on the conference call. The interpreter cut me out lol, most of the wall street guys talking about how it impacts EBITDA for 2HFY20 is not forward-looking. Plus, Appen puts it out there that it will decrease.
What the crisis has told Appen is to diversify your customer base. Autonomous cars are the way, it will have to most data in the next 5 years. The miles driven by Tesla is just a barometer of how big the market can grow. Other car companies are not that sophisticated and do catalogue engineering.
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Just saw Dino's straw (WOW) Scale AI already in the space and doing data labelling for autonomous driving cars. Ok, I spoke too soon, competition is big and Scale has the lead. In saying that, more than 1 company could label the data. The datasets are massive.