README.md

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Vectara is the Agent Operating System for trusted enterprise AI: Agentic RAG with multi-modal retrieval, orchestration, 
and always-on governance so enterprises can safely operate grounded, secure, auditable agents with real-time policy and factual-consistency enforcement.

We provide simple APIs for creating AI Agents that dramatically simplifies the task of building scalable, secure, and reliable AI applications.

To learn more - here are some resources:
* [Sign up](https://console.vectara.com/signup/?utm_source=huggingface&utm_medium=space&utm_term=i[…]=console&utm_campaign=huggingface-space-integration-console) for a Vectara account.
* Check out our API [documentation](https://docs.vectara.com/docs/).
* We have created [vectara-ingest](https://github.com/vectara/vectara-ingest) to help you with data ingestion and [vectara-answer](https://github.com/vectara/vectara-answer) as a quick start with building the UI.
* Join us on [Discord](https://discord.gg/GFb8gMz6UH) or ask questions in [Forums](https://discuss.vectara.com/)
* Here are few demo applications:
  * [AskNews](https://asknews.demo.vectara.com/)
  * [Agentic Demo](https://agent-demo.vectara.com/)
* Our [Hughes Hallucination Evaluation Model](https://huggingface.co/vectara/hallucination_evaluation_model), or HHEM, is a model to detect LLM hallucinations.
  * [HHEM leaderboard](https://huggingface.co/spaces/vectara/leaderboard)
  * Our platform provides a production-grade [factual consistency score](https://vectara.com/blog/automating-hallucination-detection-introducing-vectara-factual-consistency-score/) (aka HHEM v2) which supports a longer sequence length, is calibrated, and is integrated into our Query APIs.