Your Own Private AI
As AI evolves, businesses are turning to custom LLMs to unlock corporate resources.
As artificial intelligence evolves, custom systems unlock business resources
Konosuke Matsushita was one of Japan’s greatest entrepreneurs. As the founder of a light socket company that evolved into Panasonic, he inspired legions of salarymen with his business wisdom. Twenty-five years after his death, the “god of management” was effectively resurrected as an artificial intelligence (AI) model. A chatbot trained on his writings and speeches can produce eerily lifelike Matsushita answers, according to one relative, and will eventually be used to make business decisions. It’s a dramatic example of how businesses are using AI to leverage intellectual property built up over decades.
The past few years have seen an explosion of AI applications based on large language models (LLMs) and tools such as OpenAI’s ChatGPT and Google’s Gemini. They have been used for everyday tasks such as writing text for slide decks, lessons, and articles, as well as synthesizing search results as in Google’s AI Overview that now appears with most searches.
LLMs are based on computational systems using neural network transformers that perform mathematical functions. Measured by the number of parameters they contain, LLMs learn by analyzing vast amounts of text from books, websites, and other sources. During training, the model identifies patterns, relationships among words, and sentence structures. This process involves adjusting millions of parameters—values that help the model predict what comes next in a sequence of words.
A major problem with LLMs and generative AI, however, is that they usually draw entirely from online content and thus are prone to inaccuracies. AI hallucinations, as they are called, occur when LLMs observe patterns in the data that are nonexistent, or at least imperceptible to humans.
One solution is private AI. It brings the power of LLMs inside a company, where queries are secure and limited to the company’s own data, reducing the risk of security leaks and incorrect or misleading responses. Private AI has traditionally been limited to government, defense, finance, and healthcare users, but it’s spreading to a broader spectrum of industries due to fears about intellectual property theft.
“[Private AI] brings the power of LLMs inside a company, where queries are secure and limited to the company’s own data, reducing the risk of security leaks and incorrect or misleading responses.”
Kenja KK, a member of the American Chamber of Commerce in Japan (ACCJ), is opening up the market in Japan to private AI. The Tokyo-based company offers AI solutions for enterprises that include purpose-built expert systems, incorporating a relatively new AI technology called retrieval-augmented generation (RAG).
Bearing a name coined as recently as 2020, RAG relies on a predetermined collection of content to improve the accuracy and reliability of generative AI content. Kenja offers a self-service plan for small and medium-sized businesses and a more comprehensive enterprise plan for businesses.
“Private AI is the next frontier,” said Kenja founder and Chief Executive Officer Ted Katagi, who is also chair of the ACCJ’s Marketing and Public Relations Committee. “All companies face the same issues: you have very sensitive data that you don’t want to make accessible to everybody at the same time. Private not just in terms of someone outside the company, but within the company, too. You may not want HR data to be shared with people in finance, for example. That’s an issue you want to solve, and we solve that.”
Kenja users create so-called rooms where they can upload thousands of documents or other content, organizing this into topic-specific folders. The process can be automated, and Kenja can train and fine-tune the system. For instance, it can be taught to forget certain words or trained to understand a balance sheet in order to do financial tasks such as due diligence.
“You are kind of building a wall around a set of information and telling it to only use what’s in this area,” explained Katagi. “Having 85–90 percent accuracy—which is what current generative AI, such as ChatGPT, Gemini, or Claude, will give you—is not good enough. Private AI models that are fine-tuned and query a closed set of materials can close that gap.”
Private AI is being used in surprising applications. Just as Panasonic has cloned its founder in digital form, Dr. Greg Story is using Kenja to share the teachings of another business luminary, Dale Carnegie. The self-improvement guru from Missouri wrote a book in 1936, How to Win Friends and Influence People, that still counts among the world’s all-time bestsellers. As president of Dale Carnegie Tokyo Japan, Story has been teaching Japanese businesspeople about leadership, communications, and other skills in Dale Carnegie seminars for the past 14 years. Dale Carnegie started in Japan in 1963.
Since learning about the impact of content marketing, he has built up an enormous corpus consisting of white papers, e-books, printed books, course manuals, 270 two-hour teaching modules, as well as video and audio recordings that include hundreds of podcast episodes. He has penned a series of books himself in English and Japanese that includes Japan Sales Mastery, Japan Business Mastery, Japan Presentations Mastery, and Japan Leadership Mastery.
“If you like the cut of our jib and you want a Dale Carnegie point of view and a curated, trustworthy response, we provide that through this AI.”
The material was scattered in different places, and when clients began asking for on-demand training, Story decided to get ahead of the curve by including all his company’s content in AI-curated form, something public chatbots cannot do.
“ChatGPT will give you everything it can scrape together, but it’s everything and therefore nothing,” said Story. “You get generic answers, and you don’t know if they’re trustworthy. But if you like the cut of our jib and you want a Dale Carnegie point of view and a curated, trustworthy response, we provide that through this AI.”
Story thinks the technology can benefit businesses that have substantial bodies of work to draw on, but those that don’t will get thin answers. He adds that using tools such as those from Kenja will not only help his company learn about the benefits of AI, but it will also give it an edge over competitors. He plans to roll out his AI offerings in 2025, delivering customized responses to students’ questions in English or Japanese on topics ranging from sales to diversity, equity, and inclusion.
Could there be a Dale Carnegie version of the Matsushita chatbot one day?
Kenja has begun working with Dale Carnegie’s global team to do just that, and has developed a prototype revival of Dale Carnegie’s voice, avatar, and writing style. The writing style and word generation are done with Kenja RAG AI technology.
“Carnegie became a global superstar in a non-digital world,” noted Story. “There’s no question we can get an AI to read a script generated in his style, in his voice. It’s amazing.”