Vectara

Founded 2020

Build enterprise search agents with source citations

You can use Vectara to build autonomous agents that search through your internal company files and generate answers backed by citations. The system ingests various document types like PDFs, spreadsheets, presentations, and technical logs while enforcing role-based permissions. It uses hybrid search and reranking to ground responses in your factual data, preventing hallucinations. You can deploy it across public cloud, virtual private cloud, or air-gapped on-premises setups, connecting internal data sources directly to leading large language models without facing vendor lock-in.

What Vectara does

Ingest and parse multimodal documents like PDFs and tablesConfigure role-based access control rules for data sourcesEvaluate model responses for factual consistency and hallucinationsConnect custom LLMs including Claude, GPT, and open-source modelsDeploy retrieval agents inside a virtual private cloud or data centerQuery enterprise documentation via REST API or user interfaceHybrid search combining keyword and semantic retrieval with rerankingBuilt-in hallucination detection and factual consistency scoringMultimodal document ingestion for PDFs, spreadsheets, presentations, and imagesVerifiable source citations linked directly to generated answersDeployment options for SaaS, VPC, and air-gapped on-premises environmentsRole-based access controls and automatic metadata enrichment