For users who use multiple AI chat applications such as ChatGPT, Claude, Gemini, xAI, and Perplexity, the following problems have emerged:
- Chat history is scattered across multiple services and difficult to manage.
- I’m worried that if I write important information in an AI chat, there’s a risk of information leakage.
- AI tends to overly agree with user opinions, making it less useful for decision-making.
ThinkNavi solves these problems. By connecting to various companies’ AI chat services via API, learning from the chat content between users and AI, and building a personal model (long-term memory) of the conceptual structure network model, ThinkNavi provides the following benefits:
- It allows for the centralization of chat histories from multiple AI chat services.*You can also import existing chat history.
- Because it utilizes AI chat services via API connections, there’s no need to worry about each company storing personal information. ThinkNavi’s conceptual structure network model can be self-managed within the user account.
- The personal model acts as a “mirror” that visualizes one’s own thinking. In addition, ThinkNavi provides objective advice to the user based on the personal model. This advice isn’t about giving easy answers, but rather about helping the user think better.
This allows you to confidently use AI chat as your thinking partner.
