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Four ways to reduce hallucinations in your AI agents
Sharing 4 approaches to reducing hallucinations, backed by quantitative evidence.
PlaceboBench findings: which LLM hallucinates most on pharma data?
We ran 12 of the latest LLMs against a challenging use case in Pharma. Watch to find out how often models hallucinated, why the model with the lowest hallucination rate might not be the best option, and how latency and cost should inform your model selection.
Building hallucination resistant GenAI applications in pharma
We tested 12 state of the art LLMs like GPT-5.4 or Gemini 3.1 Pro on a challenging use case in Pharma. This resulted in PlaceboBench, a benchmark on hallucination rates in Pharma. This on-demand session walks through detailed results and strategies to mitigate hallucinations.
How to create your own hallucination detection benchmarks: making of the RAGTruth++ dataset
We walk you through the process of creating the RAGTruth++ hallucination benchmark. Useful for anyone who wants to get a deeper understanding of how benchmarks are made.
AI hallucinations - reverse engineering Azure Groundedness and building your own hallucination detector
Learn how to reverse engineer Azure's Groundedness detection system and build your own custom hallucination detector for AI applications.