Search Results for "document search engine"
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Showing 2 open source projects for "document search engine"
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Turn traffic into pipeline and prospects into customersDocket is an AI-powered sales enablement platform designed to unify go-to-market (GTM) data through its proprietary Sales Knowledge Lake™ and activate it with intelligent AI agents. The platform helps marketing teams increase pipeline generation by 15% by engaging website visitors in human-like conversations and qualifying leads. For sales teams, Docket improves seller efficiency by 33% by providing instant product knowledge, retrieving collateral, and creating personalized documents. Built for GTM teams, Docket integrates with over 100 tools across the revenue tech stack and offers enterprise-grade security with SOC 2 Type II, GDPR, and ISO 27001 compliance. Customers report improved win rates, shorter sales cycles, and dramatically reduced response times. Docket’s scalable, accurate, and fast AI agents deliver reliable answers with confidence scores, empowering teams to close deals faster.
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The AI workplace management platformBy combining AI workflows, predictive intelligence, and automated insights, OfficeSpace gives leaders a complete view of how their spaces are used and how people work. Facilities, IT, HR, and Real Estate teams use OfficeSpace to optimize space utilization, enhance employee experience, and reduce portfolio costs with precision.
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tinysearch
Tiny, full-text search engine for static websites built with Rust
tinysearch is a lightweight full-text search engine designed specifically for static websites, offering fast and efficient search capabilities without requiring a backend server. It is written in Rust and compiled to WebAssembly, allowing it to run entirely in the browser while maintaining a very small footprint. The engine uses compact data structures such as XOR filters to efficiently index and query text, significantly reducing memory usage compared to traditional search libraries. ... -
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Voy
A WASM vector similarity search written in Rust
Voy is a lightweight WebAssembly-based vector similarity search engine written in Rust that enables semantic search capabilities directly in browser or edge environments. It is designed to operate on embeddings generated from text or other data, allowing applications to perform meaning-based search rather than simple keyword matching. The engine uses efficient data structures such as k-d trees to index vectors and perform fast nearest-neighbor queries, making it suitable for real-time search experiences. ...
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