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  • Turn traffic into pipeline and prospects into customers Icon
    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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  • The full-stack observability platform that protects your dataLayer, tags and conversion data Icon
    The full-stack observability platform that protects your dataLayer, tags and conversion data

    Stop losing revenue to bad data today. and protect your marketing data with Code-Cube.io.

    Code-Cube.io detects issues instantly, alerts you in real time and helps you resolve them fast. No manual QA. No unreliable data. Just data you can trust and act on.
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    Skiplist-CPP

    Skiplist-CPP

    A tiny KV storage based on skiplist written in C++ language

    ...The project supplies a compact codebase with a clear separation between the skip list implementation and the storage operations that use it. Beyond in-memory operations, it demonstrates persistence through data dump to disk and reload, turning the structure into a tiny embeddable database. Stress-test scripts and example binaries are provided so you can benchmark throughput and validate correctness on your own machine. This makes the repo valuable for learners studying database internals and for practitioners who want a starting point for an embedded KV engine or educational experiments.
    Downloads: 0 This Week
    Last Update:
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