©2026 Business Next Media Corp. All Rights Reserved. No.102, Guangfu S. Rd., Da'an Dist., Taipei City 106, Taiwan
Beyond the Cloud: Securing Your Data with Tallgeese AI's Local AI Systems
At this year's Apple WWDC (2024), the highlight was "Apple Intelligence," which was Jeffrey Lai's last project at Apple. "I finished this project before starting my own company," said Jeffrey Lai, co-founder and CEO of Tallgeese AI, with a smile.
Jeffrey Lai was a senior employee at Apple, starting in 2011 and being responsible for the development of the Chinese version of Siri. He has extensive first-hand experience in AI, machine learning, and NLP (natural language processing). Now, he has chosen to venture into entrepreneurship, founding Tallgeese AI with a focus on artificial intelligence, allowing businesses to upload confidential data to the cloud and train generative AI applications in their own data centers.
After nearly 13 years at Apple, why did Jeffrey Lai decide to embark on the entrepreneurial path?
From WebEx to Apple: The Journey of Jeffrey Lai Influenced by Zoom's Founder Eric Yuan
Before joining Apple, Jeffrey Lai worked in the video technology team at Cisco WebEx, where the team leader was Eric Yuan, the founder of Zoom.
"He (Eric Yuan) influenced me a lot. When he was about to start Zoom, he even asked if I wanted to join him," Jeffrey Lai said with a smile. Eric Yuan's enthusiasm for entrepreneurship planted a seed in Li Jiajun's heart, but he ultimately decided to join Apple because they were developing the Chinese version of Siri. "I thought the environment would be similar to a startup, and I was very optimistic about AI technology."
This stint lasted 13 years. During his career at Apple, Jeffrey Lai realized two things: first, if he continued to develop AI within Apple, he would ultimately only serve the iOS ecosystem; second, "privacy is very important," which was one of the main themes at this year's WWDC. "When developing Apple Intelligence, I knew we were creating an on-device offline Siri, allowing users to keep their data to themselves. Privacy is not just a pain point for iPhone users."
These two realizations, combined with his long-standing desire to start his own business, led him to establish Tallgeese AI this year. But who would be Tallgeese AI's customers? Co-founder Lman Chu provided some insights.
Ensuring Privacy while Enhancing AI Performance
Jeffrey Lai and Lman Chu met through a previous blockchain project. When Lman Chu heard about Tallgeese AI's plan, he immediately thought of industry issues he had been following.
"We noticed that in traditional manufacturing, the sales model is two-phased: first, salespeople generate customer interest, then PMs provide detailed explanations to customers because salespeople are not familiar enough with the manufacturing processes," Lman Chu explained. Traditional manufacturing industries such as fishing gear, lighting, and motors often have salespeople who find it challenging to provide complete information due to cross-domain or frequent job rotations.
Although the information on these products is extensive, the production process is standardized and ISO 9000 certified, meaning there are detailed data for each product while also being highly concerned about competitive espionage. This is where edge AI can shine.
Tallgeese AI's solution has two main features: fully on-site edge computing hardware and drag-and-drop No-Code AI training software. By installing Tallgeese AI's hardware and software, users can log in to train AI, with the training process being very user-friendly—just drag and drop files. Currently, AI is fine-tuned using large language models like GPT, Gemini, and Llama.
Jeffrey Lai stated that the competitive edge of this service lies in privacy protection and accuracy. Tallgeese AI's language models only train on the data provided by the enterprise and do not respond to information outside the training scope, achieving an accuracy rate of 95.6%. The hardware design ensures the privacy of the enterprise, leveraging Jeffrey Lai's past AI training experience at Apple.
From Taiwan to Asia: Tallgeese AI's Strategic Expansion
"I'm actually half Taiwanese, so all our hardware suppliers are in Taiwan," Jeffrey Lai said with a smile. Although he was born in Hong Kong and immigrated to the US, his mother is Taiwanese, and his family now lives in Taiwan. With Taiwan playing a crucial role in the AI wave and potential customers concentrated in the Asian market, Taiwan is an important base for Tallgeese AI.
Lman Chu added that Tallgeese AI's current business model involves selling to end customers through agents and system integrators, with an annual subscription fee. They already have over 10 end customers, including traditional industry sales and university professors.
Tallgeese AI recently completed a $500,000 angel round of funding and is also part of NVIDIA's Inception program. What are their next steps besides expanding their customer base? "We plan to train AI to interpret images and videos because product information isn't limited to text," Lman Chu said.
Tallgeese AI is representing a significant leap forward in advanced robotics solutions for automating business processes. With a focus on privacy and precision, Tallgeese AI allows businesses to integrate AI into their operations seamlessly, ensuring that sensitive data remains secure while enhancing efficiency and productivity. By combining Jeffrey Lai's extensive experience in AI and Lman Chu's insights into industry needs, Tallgeese AI is positioned to revolutionize how businesses utilize AI technologies.
©2026 Business Next Media Corp. All Rights Reserved. No.102, Guangfu S. Rd., Da'an Dist., Taipei City 106, Taiwan