FeaturedRetrieval Augmented Generation
Think building your own Retrieval-Augmented Generation (RAG) system will give you a competitive edge? Think again. Companies are sinking months and hundreds of thousands of dollars into in-house AI projects, only to end up with sluggish, unsecure, and overpriced systems that can't hold a candle to existing solutions.
Read more
In highly regulated enterprise environments, predictability is non-negotiable: the same question to your RAG application should return consistent answers every time. With Open-RAG-Eval’s new Consistency-Adjusted Index, you can now precisely quantify that level of reliability.
Introducing the Open RAG Benchmark: A revolutionary, multimodal dataset built from arXiv PDFs to elevate RAG system evaluation with real-world text, table, and image understanding.
The Open Evaluation website makes it easier for you to spot the patterns within an Open RAG Eval evaluation report and take effective steps to improve your RAG system.
AI agents have the power to transform enterprise workflows—but without proper safeguards, they can easily go off course. In this blog, we explore the growing need for Guardian Agents like Vectara’s Hallucination Correction Agent
HCMBench is Vectara’s open-source evaluation toolkit designed to rigorously test and compare hallucination correction models. With modular pipelines, diverse datasets, and multi-level evaluation metrics, it gives developers a powerful, standardized way to measure and improve the accuracy of RAG system outputs.
AI hallucinations create significant business risks and erode user trust. Vectara's Hallucination Corrector (VHC) identifies inaccuracies, suggests fixes, and provides essential guardrails for your AI applications.
We’ve created a trusted platform for building safe and reliable AI applications and continue to invest in features that improve reliability, accuracy, and flexibility. Today, we're taking another step forward by introducing two powerful new capabilities: the Hallucination Evaluation Model (HHEM) and OpenAI Chat Completions endpoints.
In financial services, transformation isn’t optional. It’s constant. Regulatory pressure, digital-first customers, and fractured data landscapes have created a race for real-time intelligence and faster, smarter decisions.
Every year, governments and agencies roll out thousands of pages of new rules, policies, and updates. For businesses and public institutions trying to keep up, it’s become a massive, expensive problem.
Connect our community channel.
Join our discussion channel.
Get news, company information.
Adopt best practices in projects.
Suggest your own ideas.
Ask your follow-up questions.
