Agentic AI, Three Ways: DIY, Platforms, or Vertical Apps – When to Use Which
Agentic AI has moved from lab demos to board-level priorities, and most teams now face a familiar decision: build, buy, […]
How Does RAG Work? Unlocking Real-Time AI Insights
In today’s fast-paced digital world, AI applications must deliver not just intelligent responses—but relevant, real-time insights. Traditional large language models
RAG Pipelines & Function Calling
Introduction Typical examples of function calling in cookbooks include the ability to make calls to do web search, get weather,
Advanced Search Capabilities in Dataworkz: Hybrid Search
Key to the success of RAG systems is the quality (relevance) of the information retrieved. Traditionally, search systems have relied
RAG Applications: Query Retriever
The goal is to extract enough related and relevant information so that the downstream LLM can provide a meaningful response
RAG Applications: Query Rewriting
GenAI applications such as Question-and-Answering systems or Semantic Summarization based on RAG pipelines enable users to ask questions of private,
RAG Applications: Input Guardrails
The flexibility of these free-form queries has the potential to unlock the ability to make enterprise data become more available
A/B Testing Strategies for Optimizing RAG Applications
These applications involve a series of steps within the pipeline, requiring meticulous attention to detail to ensure optimal performance. Dataworkz
