Vectara

Vectara is a platform for building AI assistants and agents that answer from a company's own documents, using retrieval-augmented generation (RAG), which grounds an AI model's answers in your content rather than only its general training. Teams upload company content, then connect retrieval and generation steps through its API. Vectara has its own models for this, called Boomerang and Mockingbird, or teams can plug in an outside model like ChatGPT, Claude, or Gemini. It includes evaluation tools that catch and reduce hallucinations, meaning wrong answers stated with confidence. The platform holds SOC 2 Type 2 and HIPAA-related certifications and offers three deployment types: software-as-a-service, private cloud, and on-premises.

This fits a company with development resources that wants to build a custom AI assistant or agent on its own content rather than buy a pre-built search product, and that cares about measuring and reducing hallucinations, such as a regulated industry where wrong answers carry real risk. Vectara publishes starting prices: a single SaaS deployment starts around $100,000 a year, private cloud around $250,000, and on-premises around $500,000, as starting figures rather than final quotes. That pricing puts it well above simpler search tools, so it suits a company already committed to building an AI product, not just buying one. Confirm what counts as one deployment and what usage limits apply before planning a budget around these numbers.