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Assembled is the only unified platform for staffing and managing your human and AI support team.
AI for world-class support operations
Assembled is the only platform that unifies AI agents and intelligent workforce management to power fast and flexible support operations. Built for scale, we help teams automate over 50% of customer interactions, forecast with 90%+ accuracy, and optimize staffing across in-house and BPO teams. Orchestrate every chat, email, or call, balancing workloads between human and AI agents in real time — without sacrificing quality or control. Trusted by Stripe, Canva, and Robinhood, Assembled transforms support from a cost center into a strategic advantage. Our Workforce and Vendor Management tools connect forecasting, scheduling, and performance for smarter staffing decisions. AI Agents automate conversations across channels with your workflows and brand voice. AI Copilot empowers agents with real-time guidance, suggested replies, and one-click actions for faster, higher-quality resolutions.
This is a simple Port Flooder written in Python 3.2
Use this tool to quickly stress test your network devices and measure your router's or server's load.
Features are available in features section below.
Moihack DoS Attack Tool was the name of the 1st version of the program.
Moihack Port-Flooder is the Reloaded Version of the program with major code rewrite and changes. Code is much smaller in size now - from about 130 pure lines of codes to 35 lines only.
To run it you must have Python 3.2 or newer installed.Tested this on Windows,but guess it will work in Linux also,since there are not any OS specific lines in the code.
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The DDoS Attack Defender Tool is a simple, yet effective python script that defends your linux system against a distributed denial of service (DDoS) attack by limiting the number of connections per IP Address.
A privacy-first API that predicts global consumer preferences
Qloo AI adds value to a wide range of Fortune 500 companies in the media, technology, CPG, hospitality, and automotive sectors.
Through our API, we provide contextualized personalization and insights based on a deep understanding of consumer behavior and more than 575 million people, places, and things.
This project automates the reporting of improper Internet use by the X-ARF format. The two schemas specified abuse_login-attack and abuse_malware are currently implemented. Fixing a Bug and the Date / Timestamp issues. Now it should work fine :)