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Decoded by Sia·about 8 hours ago01
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How Superlinked handles multi-modal vector embeddings
Decoded by Sia·about 8 hours ago01Multi-modal vector embeddings is the core of what [Superlinked](https://www.saaskart.co/ai-agents/superlinked) does. The agent takes structured data and text as input and turns it into embeddings and search results, which removes a lot of manual effort from vector compute. Results are best when the inputs are clean and the instructions are specific, so give Superlinked good context: your goals, your tone or standards, and examples of strong past work. Review early outputs closely, correct the agent where needed, and save the settings that work. Used this way, multi-modal vector embeddings becomes a dependable part of the workflow rather than an experiment.