Why is the idea of simply uploading documents becoming increasingly powerful? The traditional approach of knowledge graphs, often compared to relational databases, has a major limitation: they require pre-defined structures like entity types and relationships. This creates a steep learning curve for dealing with unstructured content such as PDFs, emails, or notes. 🤯 However, Vertical Knowledge Platform offers a different solution by employing a vector-based graph built on embeddings. Instead of rigid schemas, this approach allows for automatic relationship discovery through vector similarity, making it significantly easier to work with messy information. 📈. 🔎
Here’s what makes the difference:
◻️ No upfront schema – Start building immediately.
◻️ Automatic relationships – Discover them via vector similarity.
◻️ Native support for unstructured text – Documents, notes, and articles are seamlessly integrated.
◻️ Natural LLM integration – Simple REST API with semantic search.
◻️ Continuous uncertainty – Similarity scores from 0.0 to 1.0 capture the nuances of the data.
◻️ Full flexibility – The same engine works across any domain and any type of content.
Imagine a library where you simply throw in your books, and an AI librarian effortlessly finds what you need when you ask—your documents become a live knowledge graph with less effort and more control. The ability to upload and easily access relevant information makes the process faster, more intuitive, and far more adaptable for today’s dynamic workflows.