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Visibility and Control: Vectara’s Admin Center
The new Vectara Admin Center provides a centralized, intuitive interface for on-premise and VPC customers to manage their Vectara deployments. It empowers DevOps and IT Admin teams with centralized visibility and control to prevent RAG Sprawl overhead.
HCMBench: an evaluation toolkit for hallucination correction models
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.
Vectara's Hallucination Corrector
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.
New HHEM and OpenAI chat completions endpoints
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.
Introducing Mockingbird 2 - Vectara’s crosslingual grounded generation model
Introducing Mockingbird 2: our latest grounded generation model optimized for RAG with advanced crosslingual support and improved performance. It runs securely in any environment—SaaS, cloud, or on-prem—delivering high-accuracy responses without data leakage risk.
Introducing custom text encoders on Vectara
We’re excited to announce custom text encoders, empowering users to integrate their preferred text embedding models directly into Vectara. This enhancement offers greater flexibility and control over the text processing pipeline, accommodating various project requirements.
Create LLM: integrate your own language model with Vectara
Now you can integrate the language model of your choice into Vectara while keeping existing security approvals, fine-tuning efforts, and AI investments intact. Use Vectara’s query and chat APIs while maintaining control over your model choices.
Improved Search with Vectara Query Rewriting (Tech Preview)
Vectara's Intelligent Query Rewriting (Tech Preview) improves RAG search accuracy by separating queries into their natural language and filter expression components.
HHEM: expanded language support
Vectara’s Hughes Hallucination Evaluation Model (HHEM) now supports 8 languages, expanding from English, German, and French to include Portuguese, Spanish, Arabic, Chinese - Simplified, and Korean.
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