
Viktor is an AI-powered coworker built to live natively inside Slack and Microsoft Teams and handle complex tasks autonomously. Equipped with its own cloud computer, Viktor can write and execute code, build and deploy applications, analyze metrics, and manage workflows across more than 3,000 integrated tools. It proactively monitors systems, flags issues, and suggests actionable next steps instead of simply responding to prompts. Teams can request reports, create tickets, audit marketing campaigns, or retrieve analytics directly within Slack conversations. Viktor maintains persistent context over long-running projects, coordinating tasks and deadlines across multiple weeks. It connects seamlessly to platforms like Linear, PostHog, Google Ads, and other business tools to automate cross-functional operations. The agent drafts artifacts such as documents, issues, and updates for approval before execution. With both free and enterprise plans, Viktor scales to match team workload and automation needs. Security and workspace controls ensure safe collaboration within organizational environments. By combining autonomy, integrations, and persistent context, Viktor acts as a highly capable digital teammate embedded in daily workflows.
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Assembled combines AI agents with advanced workforce management to give support teams the speed, flexibility, and control they need to excel. Our platform streamlines staffing for both in-house and outsourced teams, delivers forecasts with over 90% accuracy, and automates more than half of customer conversations. Whether it’s chat, email, or voice, Assembled orchestrates every interaction, allocating work between AI and human agents in real time. Leading brands like Stripe, Canva, and Robinhood rely on Assembled to boost performance and turn support into a growth driver. Key capabilities include scheduling, forecasting, live performance monitoring, vendor management, AI-powered chat, voice, and email agents, plus an AI Copilot that provides instant guidance, suggested responses, and rapid action tools for agents.
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PicoClaw
PicoClaw is a compact and highly efficient AI assistant engineered in Go to deliver powerful agent capabilities on extremely modest hardware. Designed to function on devices costing as little as $10, it consumes under 10MB of memory and achieves startup times of less than one second. Unlike many resource-heavy AI systems, PicoClaw prioritizes performance optimization and portability, running smoothly across RISC-V, ARM, and x86 architectures using a single binary. The project showcases an AI-bootstrapped development approach, where much of the core system was generated and refined through agent-driven processes. Users can deploy it through direct binary installation, source compilation, or Docker Compose for containerized environments. It connects seamlessly to popular messaging platforms including Telegram, Discord, QQ, DingTalk, and LINE, allowing users to interact with their assistant anywhere. PicoClaw includes structured workspace management for sessions, memory, scheduled jobs, and customizable skills. Security is enforced through sandboxed execution and restrictions that prevent dangerous commands or system-level damage. The assistant also supports periodic heartbeat tasks, asynchronous subagents, and cron-based scheduling for automation. Overall, PicoClaw delivers a scalable, low-cost AI agent framework suitable for personal assistants, smart devices, and lightweight server environments.
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ZeroClaw
ZeroClaw is a framework for autonomous AI agents developed in Rust, tailored for teams that need a rapid, secure, and highly customizable agent infrastructure. This framework is crafted as a streamlined, production-ready runtime that initiates promptly, operates efficiently, and scales seamlessly through various providers, channels, memory systems, and tools. With a trait-based architecture at its core, ZeroClaw empowers developers to easily switch model backends, communication protocols, and storage solutions simply by adjusting configurations, which minimizes vendor lock-in and enhances maintainability over time. Its design prioritizes a minimal resource footprint, being packaged as a single binary of roughly 3.4 MB and achieving startup times of less than 10 milliseconds while maintaining low memory consumption, making it ideal for servers, edge devices, and low-power systems. Security is inherently prioritized, featuring built-in sandbox controls, filesystem restrictions, allowlists, and encrypted handling of secrets, all activated by default. This combination of agility, efficiency, and robust security measures positions ZeroClaw as a leading choice for teams looking to implement cutting-edge AI solutions.
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