AI Digital Human OEM: What Small Businesses Must Know

Today, let’s have a chat about the topic of OEM in the digital human (AI avatar) industry. Since ChatGPT exploded overnight last year, AI has been booming and evolving at a dizzying pace. In just one year, AI has entered a phase of rapid acceleration. In China, digital human technology has also matured and is now highly favored by investors and the market. Many small and medium-sized investors have spotted huge business opportunities, but they lack sufficient funds and time to invest in R&D. So, they look to enter the AI race quickly through OEM — only to find themselves heavily exploited!

So, what exactly is OEM? Simply put, it’s a business model where a company with core technologies produces standardized products, then allows clients to brand them and sell them as their own. In the digital human industry, any company offering OEM services must be a source technology provider. Developing AI technologies from scratch requires massive R&D investment—ranging from tens of millions to hundreds of millions of yuan. Mastering core technologies is the lifeblood for sustainable growth in AI companies.

So, can the source code for digital humans, developed with hundreds of millions in investment, really be bought for just a few tens of thousands? Is this even real? What’s actually going on with these low-cost OEM offers flooding the market? Before answering that, let’s break down the two core processes involved in digital humans:

1. Training Process: This refers to using large datasets to train complex neural network models. It involves feeding input data into the AI, which then learns and adjusts through algorithms to perform specific tasks — like image recognition, natural language processing, or speech recognition. This is what we usually call digital human generation.

2. Inference Process: This involves using the trained model to perform logical reasoning with the knowledge it has already learned, applying it to new data to generate outputs. For example, when creating digital human video syntheses, we’re essentially using the model’s inference capabilities. This also explains why every platform charges based on usage time — the inference process is resource-consuming.

The training process is the most expensive and valuable part, representing the core lifeline of an AI company, and is rarely open to the public. The inference process, however, packages these capabilities for sale — which makes sense.

So, are the current OEM services for digital humans offered at just tens of thousands of yuan really reliable? Right now, there are mainly two types of providers:

• Those who simply repackage open-source code from overseas.

• Those who use basic face-swapping and texture-mapping codes.

These projects, often sourced from platforms like GitHub, might look impressive in demos, but they suffer from significant performance issues in actual use, rendering them nearly unusable. Therefore, when selecting an AI digital human system, it’s crucial to choose trustworthy and proven providers to ensure you achieve your expected results and commercial value.

Although there appear to be many digital human providers in China, only a handful are true technology sources. Among them:

• The big tech giants (like Baidu, Alibaba, Tencent) are unlikely to spin off their digital human technologies for OEM services, as they focus these assets on their core strategies.

• Deepbrain Tech (DeepVoice), which started with intelligent speech technology, has a natural technical edge and is one of the few likely to develop an OEM model. Their AI digital human content creation platform offers rich OEM services, particularly in avatar customization and voice cloning. These services are indeed priced in the tens of thousands range, and market demand is strong. However, what they open up is video synthesis capability (the inference process), not the core generation platform, which remains off-limits for now.

Liyuan Intelligence launched its OEM services with the goal of leveraging its technological strengths to help small and medium-sized businesses quickly and affordably enter the AI market. By sharing its market resources, Liyuan aims to accelerate deep AI applications across industries and drive sector-wide growth.

In conclusion, choosing a reliable digital human customization platform is vital. Factors like security, customization capability, and proven case studies must be considered. Liyuan Intelligence has excelled in these areas and has earned broad market recognition. However, since this industry is still in its early stages, many players lack deep technical foundations. So, consumers should proceed with caution when selecting a digital human platform to ensure they find the right fit for their needs.