Showing 2 open source projects for "text to code"

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    Turn traffic into pipeline and prospects into customers

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    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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  • Failed Payment Recovery for Subscription Businesses Icon
    Failed Payment Recovery for Subscription Businesses

    For subscription companies searching for a failed payment recovery solution to grow revenue, and retain customers.

    FlexPay’s innovative platform uses multiple technologies to achieve the highest number of retained customers, resulting in reduced involuntary churn, longer life span after recovery, and higher revenue. Leading brands like LegalZoom, Hooked on Phonics, and ClinicSense trust FlexPay to recover failed payments, reduce churn, and increase customer lifetime value.
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    Pythopad

    Pythopad

    A free Python source code editor and Notepad replacement for Windows

    Downloads: 0 This Week
    Last Update:
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  • 2
    DirDiff

    DirDiff

    Python 2.7 script, analyzing 2 directories for differences.HTML output

    Comparing two different versions of a directory with text files of any kind has never been easier. Detects deleted files, new files, files with changed name but same content and of course a side-by-side / line-by-line comparison of changed files. Number of context-lines is configurable. Here's, how to call it: >python DirDiff.py dir1 dir2 output.html or >python.exe DirDiff.py -l 3 -v olddir newdir dirdiff.html -l is the number of context lines in the side-by-side comparison. -v...
    Downloads: 0 This Week
    Last Update:
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