Ein Startup - Projekt von Silicon Valley - Managern hat 25 Millionen US - Dollar in der Seed - Runde finanziert, um ein vollautomatisches Marketing - AI - Agent für Unternehmen zu entwickeln | Premiere von Intelligence Emergence

Text by | Zhou Xinyu

Edited by | Su Jianxun

One-sentence Introduction

MAI (https://www.mai.co/) provides enterprises with a fully automated marketing AI Agent that covers functions such as advertising management, real-time dynamic optimization, and problem detection, enabling all enterprises to access advertising technologies as advanced as those used by large enterprises.

△MAI. Image source: Company's official website

Team Introduction

Wu Yuchen, the co-founder and CEO of MAI, has nearly 15 years of experience in building advertising platforms and e-commerce engines.

From 2010 to 2020, he served as the engineering director at Google, responsible for building the advertising system. In 2021, Wu Yuchen joined Instacart, an American fresh food instant delivery platform, as the vice president of engineering, in charge of the logistics platform technology, helping Instacart improve the fulfillment speed, efficiency, and reliability.

Previously, he obtained a bachelor's degree and a doctor's degree in engineering from Tsinghua University and Northwestern University respectively.

△Wu Yuchen, co-founder and CEO of MAI. Image source: Company's official website

Financing Progress

Recently, MAI completed a $25 million seed round of financing, led by Kleiner Perkins, with follow-on investments from institutions such as Gao Rong Capital and UpHonest Capital.

This round of financing will be used to expand the product and engineering teams and accelerate the R & D of the AI Agent platform.

Products and Business

MarTech (Marketing Technology) is a mature and continuously growing industry.

A survey report released by McKinsey on October 22, 2025, shows that in 2023, the global market size of MarTech reached $131 billion, with an expected compound annual growth rate of 13.3%. The market size is expected to nearly double within five years.

This means that MarTech is still a blue - ocean market full of opportunities.

However, Wu Yuchen found that there are still many gaps in the fully automated marketing solutions on the current market.

On the one hand, large enterprises have witnessed the significant boost of specially - developed big data and machine - learning solutions to business growth. However, this requires a substantial investment in technology, which has long been out of reach for small and medium - sized enterprises.

On the other hand, the standardized MarTech services on the market often can only serve specific links. It is difficult to truly achieve full - process autonomous optimization from creation, monitoring to optimization, and cannot meet the demand of small and medium - sized enterprises for performance marketing.

During the preliminary market research stage, Wu Yuchen found that the pain point of many customers lies in the growth of performance marketing, that is, "on the basis of marketing returns, how to find more effective marketing opportunities to achieve revenue growth".

What MAI aims to do, in simple terms, is to build an "AI Agent marketing army" with the marketing technology capabilities of large enterprises for small and medium - sized enterprises.

Taking performance advertising as an example, according to the actual business process, three steps are required to complete an advertising optimization:

Step 1: Analyze user consumption behavior through the data interfaces of advertising platforms, e - commerce service platforms, and the enterprise's own business. For example, through analysis, it is found that the sales volume of autumn T - shirts has decreased recently, while the sales volume of overcoats has increased.

Step 2: Make optimization decisions based on data analysis and business goals. For example, allocate more advertising budgets to overcoats and reduce the advertising budget for T - shirts.

Step 3: Implement the optimization strategy through the advertising platform tools.

△Image source: Company's provided materials

In the traditional manual - dominated performance marketing work, it takes days or even weeks to complete this entire process. However, based on the real - time analysis and decision - making of the AI Agent, MAI has compressed this process to the hourly level.

In Wu Yuchen's view, performance marketing requires long - term iteration and real - time optimization. And the AI Agent can precisely meet the demand for 24/7 opportunity discovery and real - time automatic optimization.

MAI's AI Agent platform can provide the following services for customers:

Google Ads automated management: Automatically create, monitor, and optimize advertising campaigns throughout the process;

Real - time dynamic optimization: Intelligently adjust budgets, bids, and creative materials 24/7;

Personalized business adaptation: Self - learn based on the enterprise's personalized products, customers, and goals;

Immediate problem detection: Provide timely warnings of budget loss risks, from invalid discount codes to low inventory;

Efficient scale expansion: Process thousands of products and creative variants simultaneously.

△Image source: Company's official website

When it comes to advantages, at the team - cognition level, the MAI team has many years of experience in building advertising platforms and e - commerce engines in enterprises such as Google, Amazon, Shopify, and Instacart.

Specifically regarding the product's differential advantages, Wu Yuchen said that in the 0 - 1 stage, MAI entered the "blank area" of autonomous marketing AI Agents.

Currently, most AI marketing tools on the market focus on single - point links such as keyword sorting and marketing material production.

Wu Yuchen believes that performance marketing is like an engine that needs continuous optimization. Single - point tools are components of this engine and cannot directly optimize the engine's iteration. The AI Agent system built by MAI is like an optimization engineer for this engine, continuously conducting data analysis to optimize the efficiency of this marketing engine.

While optimizing performance marketing for customers, MAI's AI Agent also builds a complete marketing data flywheel for customers, continuously improving the optimization effect.

"For example, the short - video recommendation engine becomes more personalized with use through the data flywheel." Wu Yuchen told us.

Currently, MAI has reached cooperation agreements with well - known brands such as Dreo, DrWoof, Fanka, Flamingo, NutritionFaktory, PatPat, Velotric, and Vivaia.

According to official sources, MAI Agent manages millions of dollars in Google advertising spending every month. Some customers have increased their sales by 40% based on MAI Agent.

For example, NutritionFaktory, a North American brand e - commerce company, based on MAI, achieved a three - fold increase in revenue on the basis of a more than four - fold return on advertising spend (ROAS), breaking historical records in both revenue and profit.

Founder's Thoughts

Large enterprises have achieved very substantial and repeatable performance improvements by using big data and machine - learning technologies. This is not only reflected in advertising platforms but also in search engines and content recommendation platforms.

This technology model is not widespread. Many small and medium - sized enterprises do not have the mature optimization technologies of large enterprises. Ultimately, the optimization technology teams owned by large enterprises represent a very high cost for small and medium - sized enterprises.

MAI's AI Agent can not only handle a large number of complex tasks but also, more importantly, bring data and machine - learning technologies that were previously out of reach for small and medium - sized enterprises, autonomously driving business growth and allowing enterprises to focus on product development.

Our ICP (Ideal Customer Profile) is small and medium - sized enterprises, and currently, we are more focused on the DTC (Direct to Consumer) merchant group. These merchants have a rather complex performance marketing data system and growth needs, which are exactly the scenarios that MAI's AI Agent aims to serve.

Compared with a large number of standardized tools in the marketing tool track, a good big data and machine - learning system needs to be customized according to the enterprise's business. The arrival of the AI era has made such customization possible.

AI has redefined software development. In the past, code needed to pre - define the software flowchart, specifying what to do first and what to do later.

Now, generative AI can customize the most effective flowchart according to the business scenario. This change has made customized and fully automated AI Agent services possible.

Welcome to communicate!