
Vectara recognized for model development and AI knowledge management
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Vectara recognized for model development and AI knowledge management
Read more
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.

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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.

History is repeating itself in AI. Just as enterprises once built siloed databases before embracing centralized data platforms, today’s rapid adoption of Retrieval-Augmented Generation (RAG) is leading to a fragmented mess of custom-built AI systems—what we call RAG Sprawl.

RAG Sprawl—the unchecked proliferation of Retrieval-Augmented Generation implementations across your organization—is silently eroding your AI investments. This growing problem is causing headaches for CIOs and IT departments while draining resources, compromising security, and creating inconsistent user experiences.

As enterprises rush to integrate Retrieval-Augmented Generation (RAG), many are encountering RAG Sprawl—a fragmented, resource-intensive approach that leads to security risks, inefficiencies, and mounting technical debt.

How to develop your generative AI application with seamless integration of Postman 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.

Vectara is thrilled to join the Connect with Confluent partner program, bringing real-time data streaming capabilities directly into our AI-powered platform.
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