Vectara, Generative AI Search Platform for Enterprise, Raised $28.5M Seed Round Led by Race Capital
We are excited to announce that Race Capital has led the $28.5 million seed round of Vectara, a Generative AI conversational search platform focused on the enterprise, partnering with Amr Awadallah, Amin Ahmad, Tallat Shafaat and the rest of the Vectara team.
Vectara is a LLM-powered search-as-a-service for the enterprise featuring best-in-class Retrieval, Summarization, and “Grounded Generation” that all but eliminates hallucinations. Developers can embed the most advanced NLP models for their app and site search in minutes through Vectara’s API without requiring any prior or additional knowledge of LLM or Machine Learning.
Developers simply upload their data and submit queries to get back amazing search results powered by Neural LLMs, whilst Vectara handles all of the extraction, encoding, indexing, retrieval, reranking and calibrating.
Vectara’s new Grounded Generation raises the bar as it allows users to ask questions about their data and returns a natural language summary based on relevant facts retrieved with citations to the company’s source data set. These citations support fact-checking and substantially reduce hallucinations, providing business users with the peace of mind that Vectara will only base its generative responses on the factual information — documents and other data — that they’ve provided to Vectara.
Data Privacy is Vectara’s Highest Priority
Vectara does not train its models on its customers’ data, such as indexed data or queries. By also providing client-configurable data retention, Vectara enables organizations to discard the original documents and text after they have been indexed so that no residual data from the company remains in the index.
We firmly believe that Amr, Amin, Tallat and Vectara will play a pivotal role in incorporating LLM within enterprises and revolutionize the way we interact.
Industry Veterans with Deep Domain Expertise in Search and Enterprise Cloud Software
We at Race Capital always look to partner with strong technical founders with expert knowledge and Amr, Amin and Tallat are perfect examples of this.
Prior to Vectara, Amr was the Co-Founder and CTO of Cloudera (acquired for $5B), a leading enterprise data cloud platform. He brings a wealth of entrepreneurial experience in scali
ng software and business operations.
Amin was co-author of Google’s zero-shot dual-encoder model for answer/information retrieval over large, arbitrarily-defined text corpora. He helped launch Google Talk to Books, one of the first ever use cases within Google of using neural networks for Information retrieval.
Tallat was a core contributor within the Google Knowledge Base team, one of the core teams for Google Search.
Enterprise Generative AI opportunity
The Generative AI total addressable market is expected to grow from 18 billion in 2023 to over $121 Billion in 2027. Furthermore, Generative AI is expected to reach 31% of the total AI market. This growth will be fueled by a significant increase in available datasets, advanced AI research, and the release of more powerful language models with more model parameters.
Vectara offers the perfect solution for enterprises that want to add large language model capabilities, trained on their own internal data — allowing for accurate information retrieval of internal knowledge whilst minimizing hallucinations that may occur with other generalized models.
Incumbent Market Ripe for Disruption
The global enterprise search market size was USD 4.21 billion in 2022 and is projected to grow to USD 8.85 billion by 2030.
However, incorporating multilingual keyword search with a comprehensive knowledge graph is an expensive endeavor, typically reserved for industry giants like Google. As a result, startups and smaller companies often rely on established players such as Algolia and Elasticsearch. These incumbents utilize BM25 keyword search algorithms, which were developed several decades ago, and are less effective when it comes to handling non-lookup queries.
With its Hybrid Search features, Vectara uses a combination of semantic search, Boolean, and exact keyword matching approaches to provide users with the most relevant answers regardless of a query’s length, level of ambiguity, provided context, or even language used.
Vectara offers a compelling solution for the enterprise search market, their zero-shot models enhance relevance across a wider range of content without requiring retraining. We believe that Vectara will become one one of the most advanced companies in the world in information retrieval and Grounded Generation.
We look forward to working closely with Amr, Amin and Tallat and the Vectara team to pioneer the future of Enterprise Generative AI.