Build lead generation pipelines that pull emails, phone numbers, and company details from directories, maps, social platforms. Full API access.
Generate leads at scale without building or maintaining scrapers. Use 10,000+ ready-made tools that handle authentication, pagination, and anti-bot protection. Pull data from business directories, social profiles, and public sources, then export to your CRM or database via API. Schedule recurring extractions, enrich existing datasets, and integrate with your workflows.
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Create and run cloud-based virtual machines.
Secure and customizable compute service that lets you create and run virtual machines.
Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications.
The Common Lisp Reasoner extends the Common Lisp Object System (CLOS) to incorporate a powerful rule language suitable for all kinds of reasoning tasks, vanilla XML and RDF/XML interfaces, and support for a variety of AI-related applications, such as scheduling, planning and diagnosis.
StarkOX, the first universal Open Source AI Robot Operating System. It provides easy to use hardware abstraction and commonly-used functionality.
Furthermore, strong cognitive functions, voice and pattern detection together with a new powerful scripting language provide possibilities to create and share abstract behavior patterns.
The TUM personal robotics package is a collection of libraries that aims to offer methods for personal robotic assistants to operate successfully in indoor environments.
‘intelliworm’ is a prototype simulation of a Intelligent Species of a common earth worm,which inherits human like decision making capabilities through Neural Network intelligence representation,all developed by integrating .NET with Lisp and Yacc.
CLearSharp is a clean C#-implementation of Common Lisp. The big goals are ANSI standard compliance, interoperability with Java and integration with scripting environments. This project is meant to be a sibling to CLearJ, with sharing of implementation.
CLearJ is a clean Java-implementation of Common Lisp. The big goals are ANSI standard compliance, interoperability with Java and integration with scripting environments. This project is meant to be a sibling to CLearSharp, with sharing of implementation.