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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AestheticsPro Medical Spa Software
Our new software release will dramatically improve your medspa business performance while enhancing the customer experience
AestheticsPro is the most complete Aesthetics Software on the market today. HIPAA Cloud Compliant with electronic charting, integrated POS, targeted marketing and results driven reporting; AestheticsPro delivers the tools you need to manage your medical spa business. It is our mission To Provide an All-in-One Cutting Edge Software to the Aesthetics Industry.
Generate a CRUD app wrapping your database in seconds
Magic is a no-code/low-code CRUD generator that allows you to generate CRUD apps 100% automatically. In addition, it is a complete open-source cloud platform and IDE, allowing you to create your own virtualized cloud on top of your own server, and/or other cloud systems, editing your code from your phone if required. Magic is professionally maintained by Aista.
A build for a back end which implements managing users with MongoDB
...It is challenging not to repeat the structure of the models in the GraphQL schema, Mongo schema, and Typescript interfaces. The goal is to have one truth point for the models and extend that data when more data is needed. With NestJS 6.0.0 a code first approach was introduced. This project uses the schema first approach to be language agnostic.