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Turn traffic into pipeline and prospects into customers
For account executives and sales engineers looking for a solution to manage their insights and sales data
Docket 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.
A file format for exchanging computational models in systems biology
The Systems Biology Markup Language (SBML) is an XML-based description language for representing computational models in systems biology. Visit the project web site to learn more.
The Accelerator Markup Language (AML) / Universal Accelerator Parser (UAP) project will develop an XML based format for describing high energy particle accelerators along with associated software to convert lattice files to a standard internal struct
ProofReading Markup Language for transmission of corrections
An XML DTD & schema for a ProofReading Markup Language, and reference implementations, to provide for annotation of printed errors and their correction. PRML will be intended for use by proofreaders, editors, and others in the publishing industry.