Search Results for "machine learning"
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Showing 3 open source projects for "machine learning"
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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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Premier Construction SoftwareRated #1 Construction Accounting Software by Forbes Advisor in 2022 & 2023. Our modern SAAS solution is designed to meet the needs of General Contractors, Developers/Owners, Homebuilders & Specialty Contractors.
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MatrixOne
Hyperconverged cloud-edge native database
MatrixOne is a future-oriented hyperconverged cloud & edge native DBMS that supports transactional, analytical, and streaming workload with a simplified and distributed database engine, across multiple data centers, clouds, edges and other heterogeneous infrastructures. A monolithic database engine is designed to support hybrid workloads: transactional, analytical, streaming, time-series, machine learning, etc. MatrixOne supports seamless workload migration and bursting among different locations and infrastructures. MatrixOne provides industry-leading latency control with optimized consistency protocol. Accelerated queries supported by patented vectorized execution as well as optimal computation push-down strategies through factorization techniques. ... -
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NoisePage
Self-Driving Database Management System
NoisePage is a relational database management system (DBMS) designed from the ground up for autonomous deployment. It uses integrated machine learning components to control its configuration, optimization, and tuning. The system will support automated physical database design (e.g., indexes, materialized views, sharding), knob configuration tuning, SQL tuning, and hardware capacity/scaling. Our research focuses on building the system components that support such self-driving operations with little to no human guidance. ... -
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MoMS (Model Management System) is a model management system for statistical models, a little bit like a database management system. Instead of having tables, we have models that can be updated and queried.
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