Semantics transforms raw data into a rich, interconnected web, providing deeper context and meaning. This approach enriches LLM's, allowing for insights and decision-making that mirror human understanding. By turning data into a dynamic asset, semantics reveals hidden trends and possibilities, elevating its value and utility.
Web3 data, while publicly auditable, isn't easily readable and digestible, even by machines. Indexing services try to pull out the embedded and encoded data from blocks and transactions to make raw data viewable and readable, but it needs to go further. Semantics naturally align datasets together through common boundaries based on meaningful associations.
Harness the power of interoperable standards, no-code/low-code productivity, and data lineage traceable from design, to code, to production. Benefit from a low-cost, hallucination-free, auditable, and more consistent AI models. Developers enjoy streamlined AI models that require fewer resources to run on, while giving better, more consistent answers.
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