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.
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Data management solutions for confident marketing
For companies wanting a complete Data Management solution that is native to Salesforce
Verify, deduplicate, manipulate, and assign records automatically to keep your CRM data accurate, complete, and ready for business.
wxMEdit, Cross-platform Text/Hex Editor, Improved Version of MadEdit
•Added automatically checking for updates
•Added bookmark support
•Added right-click context menu for each tab
•Added purging histories support
•Added selecting a line by triple click
•Added FreeBASIC syntax file
•Added an option to place configuration files into %APPDATA% directory under Windows
•Improved support for Find/Replace
•Improved Mac OS X support
•Improved system integration under Windows
•Improved encoding detection result
•Improved Hex editing support
•Added more...
XMLStarlet is a set of command line utilities (tools) to transform, query, validate, and edit XML documents and files using simple set of shell commands in similar way it is done for text files with UNIX grep, sed, awk, diff, patch, join, etc utilities.
Often I have seen some Huge Maintenance Projects it is always very difficult to track the incremental files for each release and If we want to do that we need to checkout both the branches and use some UI based tool to get the diff of the files finally we end up waiting in front of the PC for a long time and do this job. In many cases we spend more than 2 hrs/day. The time increases if there are more such parallel releases and at the end of the day 1 developer does it as full time job and...