This article is part II of our analysis on Megvii, check out part I before you read.
The service business: an albatross around the neck – and a future chokepoint
AI is creating a new type of business that contains elements of both software and services.
Some very successful SaaS products attract customers and keep growing exponentially without spending more on customer acquisition. Leveraging virality – as VCs call it – SaaS companies scale fast while maintaining acquisition costs that change little. Compared with SaaS, services can be a bad business, but AI startups like Megvii have reasons to target the niche. Previous key trends benefitting AI applications and secular growth potential in government IT spending and public security are now a bit clichéd. We focus on the business side here.
Services revenues weigh on gross margins as it is naturally not as scalable and has low margins. Though Megvii claims its IoT solutions involve the integration of hardware, algorithms and IoT devices, we consider this to be a service-heavy business due to the implementation model (as well as financials) falling perfectly with service business definition. Megvii city IoT solutions contributed to 73% of total revenues in 2019H1 while the gross margin sat at 59% in 2019H1. Comparing products and licenses, services have a variable personnel component that adds pressure to the margins. As of June 30, 2019, Megvii had 222 system integrators out of a total of 339 domestic customers that have contracts with the company for its City IoT solutions business.
- A crowded competitive landscape. Among the top bidding-winners of the Xueliang project (Chinese official long-term security plan for cities and communities) China Telecom, China Mobile and China Unicom are dominant, followed by such large security system integrators as Hikvision, Vimicro and Tsinghua Tongfang (600100:SH), according to Chinese tech media company Tedahao (in Chinese). Some of them, along with traditional players that focus on offering hardware products, have started to enhance their software abilities. Hikvision and Dahua, two leading surveillance camera vendors in China, pivoted toward other solutions several years ago. In 2018, they announced the strategy to navigate the business – Dahua’s heart of the city (HoC) and Hikvision’s AI Cloud. Hikvision has been catching up, for instance. Its central control product revenue has been taking up a larger proportion of the total revenue of the company, rising from 13% in 2016 to 15% in 2019H1. Dahua, a smaller one, has also been accelerating its solutions business since 2016 as well.
- Megvii’s first-generation solutions roadmap was primarily driven by government use cases. It offers a full-stack IoT product that is heavily used by government agencies to enhance public security, optimize traffic management and improve urban resource planning. The government continues to be a big part of Megvii’s business, but its strategic focus has shifted toward commercial customers. The revenue mix-shift from the government to commercial poses several risks/opportunities to the business. Enterprise asks for more highly standardized products. Megvii’s gross margins are expected to rise as the proportion of personnel expenses (say, consulting, implementation, delivery) used by each new client declines. We also notice that expanding into sectors such as retail and manufacturing and building mindshare. There will be a significant advantage for a company. To solve a strategic problem and build up industry, know-how could likely yield a deep moat.
What’s the future of AI businesses and players?
Part of the answer lies in the move Megvii made earlier in 2020. Megvii is trying to leverage the open-source deep learning framework MegEngine, part of Megvii’s proprietary AI platform Brain++, to allow everyone to feed data and train their AI frameworks on it. Google’s TensorFlow and Facebook’s PyTorch hold 95% of share in this market, with an array of new players joining in.
Megvii’s project Hetu is a logistics-focused platform that fits for different software systems (ERP, WMS, MES) and hardware devices (sensors, robots, AGVs) by using APIs, which has led the company to a new strategic direction.
More and larger contracts with government or retail are not the ultimate goal. AI’s potential is set to change so many industries, and the best way to ride the wave is to build an operating system. The system combines data with AI approaches, like machine learning and deep learning. It keeps absorbing customer data (generated from business projects and open platforms) as well as market data (users of open-source platforms) and training these data on the system, which drives a virtuous cycle of data. As a result, that trap of data network effects mentioned before can be mitigated and a flywheel of intelligence can be set running – the model will be better, as will the product.