graph based long term memory for ai and applications
For b2c, b2b, b2prosumer
How is the score calculated?
To determine whether an idea is "Muck" or "Brass," we consider three key factors:
1). Is the search volume increasing? It’s advantageous to be in a growing market.
2). Is there significant competition? While competition can validate an idea, too much of it can make it difficult to stand out.
3). Are enough people searching for the relevant keywords? If search volume is too low, building a business around the idea may be challenging.
Of course, startups aren’t an exact science—very little people were searching for "couch surfing" when Airbnb first launched.
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Prompt
Copy-paste the following prompt onto Marblism to build this app
Our graph-based long-term memory software addresses the core challenges faced by B2C, B2B, and B2Prosumer users, such as information disorganization, retention gaps, and context loss. For B2C, it offers personalized insights, helping consumers quickly access relevant information and enhancing user engagement through adaptive learning. In the B2B sphere, it streamlines knowledge management, allowing teams to retrieve historical data and insights effortlessly, which boosts collaboration and decision-making efficiency. Key features include dynamic retrieval of context-aware information and seamless integration with existing applications, ensuring a cohesive user experience. For B2Prosumer users, our solution empowers them to harness their growing knowledge and insights effectively, transforming casual insights into actionable goals. With advanced visualization tools, users can track their learning progress and make informed decisions based on data relationships. The software's intuitive tagging and organization capabilities minimize the risk of forgotten information, catering to users who need both organization and flexibility. Ultimately, our graph-based long-term memory enhances productivity across all segments by bridging the gaps in understanding, retention, and knowledge utilization.