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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Atera all-in-one platform IT management software with AI agents
Ideal for internal IT departments or managed service providers (MSPs)
Atera’s AI agents don’t just assist, they act. From detection to resolution, they handle incidents and requests instantly, taking your IT management from automated to autonomous.
PBS Cluster Viz is a project to display information useful to admins and users about a computing cluster managed by a PBS-compatible resource manager. Information includes load and job distribution. Interactive as well as static output is available.
DISTributed Adaptable Executable (DISTae) is a software layer that allows the portability of programs among different heterogeneous computing units and run the different parts of the code simultaneously in a distributed and heterogeneous environment.
This Project aims to create a Linux Distribution focused on the IBM zOS system, it includes a set of Mainframe tools, based all in Linux Kernel modules, C and Python.
-MainFrame Access Methods
-ISPF menus
-REXX scripting
-RACF security
-JCL Batch Job
Java based multi-agent platform built on an organizational model (agent, group, role). MadKit provides general agent facilities (lifecycle management, message passing, distribution, ...), and allows high heterogeneity in agents.
TOS is a lightweight distributed computing middleware platform. It provides a secure message passing mechanism and a simple framework for implementing application specific message handlers (extensions).
StreamMine is a distributed event processing (streaming) infrastructure.
You can create low-latency, fault-tolerant stream processing functionality with any stream-oriented operators that can be implemented in Python.