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.
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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.
AI Assistants and Agents are revolutionizing financial services, offering hyper-personalized customer experiences, operational efficiencies, and enhanced risk management. Explore how Vectara’s GenAI and RAG-powered platform enables financial institutions to embrace this new wave of intelligent, autonomous technology securely and effectively.
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.
Open RAG Eval is an open-source framework that lets teams evaluate RAG systems without needing predefined answers, making it faster and easier to compare solutions or configurations. With automated, research-backed metrics like UMBRELA and Hallucination, it brings transparency and rigor to RAG performance testing at any scale.
Vectara's new open-source framework for comprehensive RAG evaluation, open-rag-eval, represents a significant leap forward in ensuring that AI systems deliver accurate, relevant responses.
The ultimate C-suite upgrade. Fire your human boss, hire an agentic CEO. Zero exuberant salary, 100% uptime, infinite buzzwords!
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.
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