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.
Learn More
Dun and Bradstreet Connect simplifies the complex burden of data management
Our self-service data management platform enables your organization to gain a complete and accurate view of your accounts and contacts.
The amount, speed, and types of data created in today’s world can be overwhelming. With D&B Connect, you can instantly benchmark, enrich, and monitor your data against the Dun & Bradstreet Data Cloud to help ensure your systems of record have trusted data to fuel growth.
Wapiti is a vulnerability scanner for web applications.
It currently search vulnerabilities like XSS, SQL and XPath injections, file inclusions, command execution, XXE injections, CRLF injections, Server Side Request Forgery, Open Redirects...
It use the Python 3 programming language.
C/C++ , PHP, PYTHON, 3D ENGINES, CHROME NATIVE CLIENT
+ C/C++ and PHP projects, Python and Others
+ 3D ENGINES
+ Videogames Projects based in Bennugd
http://www.bennugd.org
Web Page
https://coldev.sourceforge.io/