Neeva

Overview

Neeva is an AI search engine that, like Microsoft's NewBing, merges traditional web search with conversational AI. It seamlessly integrates AI Q&A into the search experience, allowing users to ask questions in natural language and receive direct, synthesized answers. Instead of presenting a simple list of links, Neeva understands the intent behind queries and surfaces the most relevant information instantly, making search both faster and more intuitive.

A key differentiator of Neeva is its dedication to transparency and credibility. Every AI-generated response is accompanied by explicit citations of the information sources used, enabling users to verify the accuracy of the content and trace it back to its origin. This source-annotation system builds trust and helps users feel confident in the answers they receive. By making citations an integral part of the answer, Neeva empowers users to quickly cross-reference facts and delve deeper into the original sources, promoting a more informed browsing experience. Whether you are conducting academic research, checking facts, or simply exploring a topic, Neeva offers a smarter, more reliable alternative to conventional search engines.

Core capabilities

LLM-Powered Answer Summarization

Neeva integrates large language models into its search pipeline to synthesize concise, cited answers from multiple ranked web sources, reducing the need for users to manually scan result pages.

Retrieval-Augmented Generation (RAG) Architecture

The system combines live web index retrieval with generative language models, enabling grounded responses that reference underlying documents while minimizing hallucinated or out-of-context content.

Privacy-By-Design Search Stack

Neeva is engineered to avoid persistent search-history storage, IP tracking, or device fingerprinting, ensuring that no long-term behavioral profile is built from user queries.

Ad-Free Organic Result Ranking

The search engine eliminates sponsored listings and prioritizes content based on relevance and quality signals, preventing advertiser influence from altering the natural relevance model.

Personal Data Connectors

Users can link first-party data sources such as email, documents, and calendars, allowing the retrieval system to incorporate private context into personalized search results without exposing that data to the public index.

Subscription-Based Commercial Model

Neeva employs a paid-subscription revenue mechanism instead of advertising, aligning product incentives with accuracy and user privacy rather than engagement-driven ad targeting.

Use cases

Extract key findings and citations from papers quickly for academic research

Get accurate answers instantly without ad clutter for everyday information queries

Privacy-conscious users can search sensitive topics without worrying about being tracked

Solve complex problems like travel planning through conversational search

Teachers search teaching materials and get AI summaries to speed up lesson preparation

Enterprise teams search internal documents, requiring cloud drive integration

Compare product prices before shopping without misleading ads