Introduction

In the ever-evolving landscape of robotics and AI technology, the potential for transformation remains boundless. To build a successful robotics startup using AI techniques, the founders need to understand the following things:

Identifying significant and unmet market needs. Utilizing a mature Utilizing a mature hardware supply chain to reduce costs. Developing advanced robotic systems and AI models to build a competitive advantage.

Identifying large and unmet market needs

It’s important to identify market needs that aren’t being met at the beginning of building a robotics company. In my personal experience and my conversation with fellow entrepreneurs, there are two common pitfalls a lot of founders with technical backgrounds will fall into: (1) Use the technical solution to find the feasible problem and (2) fake market need or market need too small.

Roboticists are always excited about how to build highly automated robotic systems that can look cool and fascinating. However, the startup might find out that there is a long journey to find target customers to buy this type of product. Even if they find some customers interested in the purchase, the market might not be large enough to support the company to grow and scale. A lot of times, there is a gap between what the users need and what the startup has already built. If the founders don’t want to raise a lot of money to dilute their equity or burn a lot of cash to find the correct product-market fit, it’s always better to start with what the user/market wants and then think about how we can build the product around it. A lot of times, don’t fall into the trap that it’s always best to use the robot to solve the problem because we are roboticists. The answer is that it is not always true. If we can use a more accessible and cost-effective solution to solve the problem, we should go for that first.

I want to clarify that I don’t disagree with the idea of using technology to identify market needs. However, sometimes there isn’t a market simply because there isn’t a product that meets people’s needs. These untapped markets are waiting to be discovered or created by innovative founders. While many people have ideas about what the future should look like, only a select few can truly envision it. Successful founders have a clear vision and a strong drive [1] to build the future they envision, and they understand what it will take to make that vision a reality. While this path can be rewarding, it requires patience and careful execution of a strategy that can adapt to changing circumstances.

Here are some common ways for founders to identify the market needs and user pain points.

When developing a consumer product, it is crucial to conduct thorough market and user research. One effective source for identifying a relevant pain point is the experience of the founder, who likely serves as both the user and builder of the product. However, founders must ensure they can generalize their identified pain points to the broader consumer population. For example, if busy and tech-avid founders live in suburban housing with a large lawn area to clean up. They need to get help from lawn cleaning services. However, the current market has labor-cost lawn cleaning services and traditional mowing machines. An automatic robotic lawn mower would be an ideal product for the founder to build and purchase; they can see through this need as both builders and users.

Founders need to consider from a different perspective if they are building automation machines and robots for companies. The ideal robot for enterprises is tailored to the specific industry. Founders need to actively engage or have experience in customers’ daily routines and tasks so that they can pose intelligent inquiries, attentively listen to customers’ requirements, and efficiently resolve any issues customers may encounter. In this process, founders can turn customers’ complaints and pain points into business opportunities.

After identifying the large market, founders should always begin with a specific niche direction.[2] Starting with a niche direction has two benefits: (1) Since startups don’t have many resources, founders need to be focused and agile to make sure their product is rightly needed by the customers. Too many product directions would significantly distract the founders from verifying the product need. Besides, much work related to building multiple non-key features would make it hard for founders to iterate the product quickly with less time and money. Fast iteration and improvement can greatly help when one direction fails. (2) Niche direction can put the startup into a low-key mode, so it will take potential competitors more time to discover the threats. Founders need to ensure the niche direction is solid before expanding to other directions in this vast market.

Utilizing a mature hardware supply chain to reduce costs

It is the key to reducing the hardware cost for the hardware company in the robotics domain. There are multiple benefits.

First, it can increase profit, which is essential for a business. Second, for consumer products, the cost is a significant user factor in making a purchase decision. Last, to effectively grow your business in the early stages, founders can focus on selling products to customers instead of relying heavily on investor funds. This approach works best when competition is not fierce, and business expansion is yet to be necessary. Establishing a well-developed and mature hardware supply chain is hugely beneficial in cutting down expenses. The primary advantage of such a supply chain is that it can significantly improve the manufacturing processes, thereby reducing the cost of producing each unit. Additionally, a well-established supply chain can help avert supply chain disruptions, which can cause significant cost implications. Lastly, a trustworthy and dependable supply chain can ensure easy access to the necessary materials and components, preventing production delays and other issues that can increase costs.

There are several hardware supply chain hubs worldwide, such as Shenzhen, South Korea, and Germany. Startups need to consider and explore practical approaches for establishing, locating, or collaborating with established hardware supply chain firms.

When deciding on a supply chain approach, weighing the pros and cons of building an in-house team versus partnering with other companies is essential. To make the best decision, consider the company’s short-term and long-term objectives and how each option can contribute to achieving those goals. Remember that the best choice may vary depending on the stage of the company. If there’s enough funding available, and the supply chain is crucial to the business, then gradually building an in-house team based on business needs and progress is a good option. However, if funding and resource constraints exist, forming partnerships with other firms might be a better approach.

Developing advanced robotic systems and AI models

Technology can create leverage for the business so that it will take a long time for other competitors to catch up. I propose a framework with three pillars regarding how a company can succeed in building its moat: (1) applied research, (2) a strong bond between hard-core engineering, user-driven product, and systematic testing teams, and (3) a commercialized platform.

Here are the reasons why these three pillars can help build competitive advantages.

Applied research.

The key to driving innovation and exploring technological feasibility lies in research. It’s rare for robotic startups to do research because it’s expensive in both time and cost. Thus, unlike research with a paper publishing focus in the academic setting, industrial applied research aims to solve big problems with a clear product-driven purpose to help customers solve their problems and improve their lives. The applied research seeks to disambiguate the engineering questions. It can also form the foundation for companies to stay ahead of the game by building core technologies for future product generations. Additionally, intangible assets like intellectual property spun from research work create hidden value that sets a company apart from its competitors. Usually, this type of knowledge is brought up by PhDs who have research focuses on specific domains throughout their study in the university or industrial veterans. For example, the team led by Professor Sebastian Thrun at Stanford University emerged victorious in the DARPA Grand Challenge, a competition aimed at developing autonomous vehicles. This achievement paved the way for the inception of Google’s self-driving car project, which later evolved into Waymo. Therefore, prioritizing applied research and keeping key talents is essential for long-term success and a competitive edge.

Strong bond between engineering, product, and testing.

Good engineering work is a channel to project some excellent research ideas into the products consumers use daily. For example, researchers usually get critical results by making a few assumptions. Due to these assumptions, some results cannot be directly used in product development or cannot be achieved as same as what is achieved in the lab environment. Engineering work is trying to incorporate both research and user research into the product so that the product is user-friendly, robust, cost-effective, and safe. Products and user interfaces are the only interfaces or media customers directly face daily instead of the research knowledge. Besides, hard-core engineering can help build a suitable-size and robust hardware and software infrastructure to support fast system updates and iterations.

User-driven product development ensures the user is always involved in testing and feedback. It allows for iterative improvements based on user feedback. Sometimes. Startups set up a co-creation session with users so that users can also be a valuable resource for generating new ideas. In this process, users foster a sense of ownership and investment in the product. Ultimately, the goal of user-driven product development is to create products tailored to the end user’s needs and preferences, resulting in higher levels of satisfaction and engagement.

The systematic testing team can create a detailed test plan that outlines the specific tests to be conducted, including the expected results and acceptance criteria. This plan can then be executed in an organized and step-by-step manner, ensuring that all aspects of the system are thoroughly tested. Additionally, it can be helpful to involve multiple stakeholders in the testing process, including developers, product designers, testers, and end users, to ensure that all perspectives are taken into account and that any issues or bugs are identified and addressed as early as possible. Ultimately, the goal of systematic testing is to ensure that the system is functioning as intended, is reliable and stable, and meets the needs and expectations of the end users.

Finally, establishing clear communication channels among the engineering, product, and testing teams is crucial to ensure iterative product development and smooth rollout like a flywheel.

Commercialized platform.

When creating a commercialized platform, it’s essential to keep the needs and preferences of your target customers in mind. You can increase customer engagement and boost revenue by utilizing an effective monetization and marketing strategy. To do it, developing a robust business model that aligns with your goals and objectives is essential. Additionally, it’s important to curate compelling branding that resonates with your target customers and tells an engaging story about your products. By selling products that are both effective and appealing, you can ensure that your customers feel satisfied and happy with their purchases. For example, you could offer robotic products that are eco-friendly, or that offer unique benefits that are hard to find elsewhere. Ultimately, the key to success in a commercialized platform is to provide value to your customers and deliver on your promises.

Based on the first two pillars, developing a solid robotic system and AI models would align with the company’s moat-building objectives. Here are some strategies to achieve this goal.

• Develop key software and hardware components using an in-house team. The startup should completely control its development and progress for the vital software and hardware components related to robotic and AI software. In this case, the proprietary technology and the value it creates for the company don’t depend on third-party companies.

• Outsource non-key tasks. To increase workflow efficiency, delegating repetitive and low-tech tasks to third-party companies meeting specific expectations and timelines is wise. For functions such as data labeling and annotation, which require low technical and operation-heavy skills, startups can outsource to a labeling company. This allows the company to focus on more important tasks while others can provide better service at reasonable prices. Before collaborating with third-party companies, it’s essential to document your needs in detail. During conversations with third parties, clearly communicate task expectations, deliverables, and timelines to ensure both parties are on the same page about what needs to be delivered and when.

• Establish partnerships with other companies. To maintain a successful and lasting partnership, it’s crucial for both parties to recognize the advantages of working together and to utilize one another’s strengths to achieve a mutually beneficial outcome. For instance, a robotics startup may collaborate with a hardware manufacturing company to create more efficient and advanced robots tailored to specific industries or tasks. The hardware firm can offer expertise in designing and constructing high-quality components, while the robotics firm can contribute its knowledge of robotic software and automation. This could lead to developing powerful robots with dependable software programs, benefiting businesses and their customers.

Conclusion

In summary, building a successful robotics startup using AI techniques involves identifying significant and unmet market needs, utilizing a mature hardware supply chain to reduce costs, and developing advanced robotic systems and AI models to build a competitive advantage. It’s crucial to avoid common pitfalls such as using technical solutions to find feasible problems or creating fake market needs. When deciding on a supply chain approach, weighing the pros and cons of building an in-house team versus partnering with other companies is essential. Founders should prioritize applied research, establish a strong bond between engineering, product, and testing teams, and create a commercialized platform to align with their moat-building objectives. Ultimately, by focusing on these critical areas, startups can create innovative products that meet the needs of their customers, setting the stage for enduring success in the dynamic world of robotics and AI.

[1] How to succeed with a startup. Sam Altman.

[2] STARTUP GROWTH by Paul Graham.

I would like to express my gratitude to Siyu Jia, Rich Cisek, and Don Fotsch who provided valuable feedback and comments.