NeevaAI

Delivers search results personalized to user context and preferences without collecting, storing, or selling user behavioral data. Uses on-device context modeling and encrypted preference profiles rather than server-side tracking pixels or third-party data brokers, enabling relevance ranking that improves with user interaction while maintaining zero-knowledge architecture where the search backend cannot correlate queries to user identity.

Enables unified search across both public web results and proprietary data stored in Snowflake data warehouses through federated query execution and result ranking. Implements secure OAuth2-based authentication to Snowflake instances, translates natural language queries into SQL via LLM-based query generation, executes queries against customer-controlled warehouse infrastructure, and merges results with web search rankings using a unified relevance model that weights internal data higher for enterprise-specific queries.

Operates a freemium subscription model where core search functionality is free but premium features (advanced filters, saved searches, API access, priority processing) are gated behind a paid tier. Unlike ad-supported search engines, revenue comes entirely from user subscriptions rather than advertiser data sales, eliminating the conflict of interest between user interests and advertiser interests. The business model is enforced through feature-level access control and usage quotas rather than data monetization.

Maintains a smaller but higher-quality search index compared to Google by applying editorial curation and content quality filters that reduce spam, misinformation, and low-value results. Uses a combination of automated quality signals (domain authority, content freshness, engagement metrics) and human editorial review to exclude low-quality sources, resulting in a smaller index (~10% of Google's size) but with higher average result quality and relevance. This approach trades comprehensiveness for precision.

Implements technical and organizational controls to enforce transparent data handling practices, including explicit user consent for any data collection, no third-party data sharing, and regular privacy audits. Uses privacy-by-design principles where data minimization is enforced at the architecture level (e.g., queries are not logged to user profiles, search history is stored locally by default, no cookies for tracking). Provides users with downloadable data exports and deletion capabilities that are enforced through database-level constraints rather than soft-delete practices.

Ranks search results using semantic understanding of query intent and document relevance rather than purely link-based signals (PageRank). Uses transformer-based language models to encode both queries and documents into semantic vector space, then ranks results by cosine similarity to the query embedding, combined with traditional signals (domain authority, freshness, engagement). This approach enables understanding of synonyms, implicit intent, and semantic relationships that keyword-matching approaches miss, improving relevance especially for natural language queries.

Provides REST API endpoints for programmatic search access, enabling developers to integrate NeevaAI search into applications, scripts, and workflows. Implements OAuth2-based authentication, rate limiting with configurable quotas, and structured JSON responses containing ranked results, metadata, and relevance scores. Premium tier users receive higher quotas and access to advanced parameters (custom ranking weights, result filtering, batch query support). Quota management is enforced through token-bucket algorithms with per-user and per-application limits.

Stores user search history and saved searches locally on the user's device by default, with optional server-side sync using end-to-end encryption. Search history is not sent to NeevaAI servers unless explicitly enabled for sync, and when synced, is encrypted with a user-controlled key that the server cannot decrypt. Enables features like search suggestions, saved search collections, and search analytics without requiring the server to have access to plaintext search history. Users can export, delete, or clear history at any time with immediate effect.