My main use case for Deepset AI Platform is utilizing it as an AI orchestration layer for RAG, search, and agentic workflows. I use this as an AI orchestration solution for GenAI applications and for AI agents. A specific example of how I use Deepset AI Platform in my GenAI application is that our primary use case is helping AI agents retrieve the right information about meetings, culture, and HR and team context before answering. For that, I am using Deepset AI Platform's orchestration layer for fetching the right information. I can confirm that Deepset AI Platform's main use case is helping AI agents retrieve relevant information.
I have been using Deepset AI Platform for around six months. I use Deepset AI Platform mainly for Gen AI model evaluation for our RAG application. For example, we are using Deepset Haystack open-source platform with a Gen AI evaluation framework called Ragas. We use Haystack to quickly assemble our RAG application pipeline to take the prompts and then interact with our vector database, which is Pinecone, and then process the query, get the response, and then compare it with the reference results provided by humans. We then use the LLM as a judge to perform evaluation and output the score for developers to see in order to evaluate the chunking strategy of their vector database.
My main use case for Deepset AI Platform is utilizing it as an AI orchestration layer for RAG, search, and agentic workflows. I use this as an AI orchestration solution for GenAI applications and for AI agents. A specific example of how I use Deepset AI Platform in my GenAI application is that our primary use case is helping AI agents retrieve the right information about meetings, culture, and HR and team context before answering. For that, I am using Deepset AI Platform's orchestration layer for fetching the right information. I can confirm that Deepset AI Platform's main use case is helping AI agents retrieve relevant information.
I have been using Deepset AI Platform for around six months. I use Deepset AI Platform mainly for Gen AI model evaluation for our RAG application. For example, we are using Deepset Haystack open-source platform with a Gen AI evaluation framework called Ragas. We use Haystack to quickly assemble our RAG application pipeline to take the prompts and then interact with our vector database, which is Pinecone, and then process the query, get the response, and then compare it with the reference results provided by humans. We then use the LLM as a judge to perform evaluation and output the score for developers to see in order to evaluate the chunking strategy of their vector database.