*** 7/16/2024 – Vectara launches Mockingbird LLM & announces $25MM Series A – Read the Press Release ***
The Trusted GenAI Platform
for All Builders.
Retrieval Augmented Generation-as-a-Service (RAGaaS) to Power Your Business.
Mitigating Hallucinations and Copyright Concerns, Minimizing Bias, Enhancing Explainability, and Broadening Cross-Lingual Reach. Your TRUSTED entry point for GenAI.
*** New Mockingbird LLM: Fine-tuned specifically for RAG scenarios ***
FREE Short Course!
Embedding Models: From Architecture to Implementation
- Join our new short course, Embedding Models: From Architecture to Implementation! Learn from Ofer Mendelevitch, Head of Developer Relations! This course goes into the details of the architecture and capabilities of embedding models, which are used in many AI applications to capture the meaning of words and sentences. In this course you will learn:
- How to use different embedding models such as Word2Vec and BERT in various semantic search systems.
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- The architecture behind embedding models; and learn how to train and use them.
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- To build and train dual encoder models using contrastive loss, enhancing the accuracy of question-answer retrieval applications.
The GenAI Product Platform
Vectara provides a Trusted Generative AI platform. The platform allows organizations to rapidly create a ChatGPT-like experience (an AI assistant) which is grounded in the data, documents, and knowledge that they have. Our serverless RAG-as-a-Service also solves critical problems required for enterprise adoption, namely: reduces hallucination, provides explainability / provenance, enforces access control, allows for real-time updatability of the knowledge, and mitigates intellectual property / bias concerns from large language models.
Extract
Vectara automatically extracts text from PDF and Office to JSON, HTML, XML, CommonMark, and many more.
Encode
Encode at scale with cutting edge zero-shot models using deep neural networks optimized for language understanding.
Index
Segment data into any number of indexes storing vector encodings optimized for low latency and high recall.
Retrieve
Recall candidate results from millions of documents using cutting-edge, zero-shot neural network models.
Rerank
Increase the precision of retrieved results with cross-attentional neural networks to merge and reorder results.
Summarize
Optionally generate a natural language summary of the top results for Q&A or AI Agent experiences.
Extract
Vectara automatically extracts text from PDF and Office to JSON, HTML, XML, CommonMark, and many more.
Encode
Encode at scale with cutting edge zero-shot models using deep neural networks optimized for language understanding.
Index
Segment data into any number of indexes storing vector encodings optimized for low latency and high recall.
Retrieve
Recall candidate results from millions of documents using cutting-edge, zero-shot neural network models.
Rerank
Increase the precision of retrieved results with cross-attentional neural networks to merge and reorder results.
Summarize
Optionally generate a natural language summary of the top results for Q&A or conversational AI experiences.
End-to-End GenAI Platform
Get Wise on Your Data with RAG-as-a-Service
Some LLMs train their models on your data. Some hallucinate when they don’t know the answers to your questions. And some lexical searches provide more relevant answers than solely semantic searches. Retrieval Augmented Generation (RAG) remedies all of this.
Our summarization is grounded in the facts retrieved from the indexed data. This means that we significantly reduce the probability of hallucination during the summarization stage; we provide an answer which is concise and sound based on the intended meaning vs. rephrasing the underlying data. With Vectara’s RAGaaS you can ensure your results are in context and hallucination free.
Simple APIs for Builders
Powerful Customization for Developers
Vectara is a modern, API-first search platform. Developer-friendly and easily accessible, all Vectara APIs are designed for consumption by application developers and data engineers who want to embed powerful generative AI into their site or application. LLMs are increasingly complex and become more complex when leveraging more than one in a pipeline or end-solution. Vectara removes the barrier to entry with a trusted entry point by allowing users to operate its platform without having to have deep technical knowledge of operating and hosting multiple LLMs. Vectara APIs abstract away the underlying complexity of operating GenAI solution.
Find The Answers You Are Looking For With LLM-Powered Hybrid Search
The way people search is changing. They ask questions. They use shorthand. They make typos. They use voice to search. Today, users ask big questions and expect amazing results, immediately. Vectara radically changes how developers build conversational AI. Developers who use Vectara do not need to address the complexity of human language from plurals, verb tenses, idioms, synonym lists, pragmatics and language packs to deliver incredibly relevant results. Users ask. Vectara answers.
Vectara Overview [PDF]
Vectara’s GenAI platform allows businesses to add hybrid search, Retrieval Augmented Generation (RAG), and conversational AI capabilities to their applications. This powerful end-to-end platform is exposed to developers via simple APIs, so the cost and implementation time remain surprisingly low.
