How an Uzbek entrepreneur bought Yandex, created an AI startup in the US

Akmal Payziyev, Menlo Park, co-founder and CEO, LinkedIn

How it started

I have been engaged in technology entrepreneurship since 2005. I am from Uzbekistan and moved to the United States in 2024. Before that, I managed to create several companies in Uzbekistan. The first company I established in 2005 was Yarmarka.uz, an online store for electronics and home appliances.

A year later, we launched Newmax Technology. It focused on creating automotive navigation systems and electronic maps. We are still the only company in Uzbekistan providing digital maps via API, which we use in projects like MyTaxi.

In 2006, we began developing Newmax Technology in the field of GPS navigation systems and vehicle fleet management systems. In 2012, I became a co-founder of Workly, a cloud system designed for time tracking. In 2015, we launched Express24, a food and product delivery service. In 2024, we sold Express24 to Yandex.

Last year, I moved to the United States to study at the Stanford Executive Program. During my studies, the final stages of negotiations with Yandex were underway, and the agreement was nearly finalized. This prompted me to embark on a new, global-scale project. I decided to focus on the field of artificial intelligence, as it is a new segment with immense opportunities. AI is already transforming all industries, and I wanted to be part of this wave.

Inspired by my experience working in the corporate sector, I began developing the idea of creating digital employees who work alongside real colleagues. I believe that in the future, people and digital employees will work together, even if they are not physically in the office. I work in Palo Alto and hold online meetings with colleagues in various cities. I am confident that digital employees will become an integral part of business.

Launching the startup

Initially, while studying at Stanford, I wanted to create digital employees for franchise networks, as my experience with Express24 gave me a good understanding of their problems. However, within three months, my co-founders and I realized that the logistics sector offered significantly greater opportunities.

The US logistics market is valued at $1 trillion, highly fragmented, and dynamic. The restaurant business, on the other hand, has low margins and is slow to adopt technologies. Furthermore, there is no absolute leader in the logistics sector.

Today, we are creating digital employees for the logistics sector: for example, digital dispatchers, HR agents, recruiters, and compliance agents, who help carriers manage their operations effectively.

The Team

Our company has grown significantly and currently consists of 12 highly qualified specialists. Our strong team of engineers has enabled us to achieve great results.

Target Audience

Our main partner is DAT, the largest Load board in the US, a company valued at $30 billion. We collaborate with DAT daily on developing AI agents. We are also partnering with TruckStop and Uber Freight, which are among the three major players in the market.

Currently, we are signing partnership agreements with companies such as J.B. Hunt and C.H. Robinson. More than 30 customers are currently testing our system.

Incubation Programs

When I arrived in the US, we participated in the Alchemist X accelerator program, managed by Silkroad Innovation Hub in collaboration with Alchemist Accelerator. This was an important milestone for us.

Regarding investments, while studying at Stanford, I expressed my intention to start a new startup in the US to my classmates. As a result, several classmates invested $100,000.

Additionally, my partners and I invested our own funds into the project and have been developing it with our own capital so far.

Challenges

Establishing relationships with major players as a new entrant to the market is one of the most difficult tasks. Without integration and proper context, it is difficult to create the necessary product.

AI agents are not just technology, but also a process of integrating into the industry and creating a quality user experience. As we saw in the example of ChatGPT, innovations in the interface can fundamentally change technology adoption.

The second challenge is integration with large companies. The logistics industry has many barriers, and large companies approach new players with caution. It took us more than four months to sign a contract with one major security company.

During this process, the Stanford network has helped me—networking with former and current students accelerates finding the necessary contacts.

Achievements

Launching the product and having ready-to-pay customers is a major achievement for us. Even during the product development stage, customers began paying us amounts ranging from $1,000 to $3,000.

The market is becoming increasingly complex, especially due to the introduction of tariffs. In the future, companies that can optimize costs will remain competitive.

We focus precisely on efficiency and optimization. A company in the US with 300 vehicles generates approximately $100 million in revenue per year, but its efficiency is low. Every 1% improvement could bring them millions of dollars in additional revenue.

Our AI agents can significantly increase company efficiency and generate over $10 million in profit per year.

Today, we have more than 40 customers who are actively supporting the development of our project.

Plans

We have big goals by the end of the year. Competition is increasing in automating brokerage processes, but we are focusing on automating carrier operations.

We plan to process thousands of orders daily with the help of AI agents and execute operations worth $200,000 per day, which amounts to $5–6 million per month.

We aim to create a system for independent booking of orders using AI agents, which will significantly increase the level of automation and efficiency.