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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Robin by Atera is an autonomous IT support solution that helps organizations resolve device and cloud-related issues automatically. The system functions as an AI-powered IT agent capable of handling support requests from employees across communication channels such as Slack, Microsoft Teams, email, and service portals. Robin analyzes incoming requests, verifies user identity through integrations with systems like Okta, Azure AD, or Google Workspace, and collects the necessary technical data to diagnose the issue. The platform can perform actions directly on endpoints, including installing applications, restarting devices, managing updates, resolving network issues, and troubleshooting system performance problems. Robin is designed to take full ownership of support incidents, investigating the problem, applying approved fixes, confirming resolution, and closing the ticket. The system continuously learns from previous incidents and outcomes, improving its ability to resolve future issues automatically. Through integrations with IT service management platforms and internal tools, Robin can execute workflows securely across an organization’s technology stack. By automating common IT support tasks, Robin helps reduce ticket backlogs, improve employee productivity, and minimize the need for additional IT staff.
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Jan
Jan is a fully open-source AI assistant platform that enables users to run large language models locally on their own devices. It prioritizes privacy by ensuring that all data remains on the user’s machine, eliminating reliance on external APIs. The platform supports multiple AI providers and models, allowing users to switch between local and cloud-based options seamlessly. Jan offers a simple and intuitive interface, making it accessible to both technical and non-technical users. It includes built-in features such as real-time web search, enhancing the assistant’s ability to provide accurate and relevant information. Users can integrate models from providers like OpenAI, Google, Meta, and Mistral, as well as open-source alternatives. The platform is designed to be lightweight, efficient, and easy to install, reducing the complexity often associated with local AI setups. Jan also aims to introduce memory capabilities, allowing the assistant to retain user preferences and context over time. It is supported by an active open-source community contributing to continuous improvements and innovation. The platform is ideal for users who want a customizable and private AI experience. Jan combines flexibility, performance, and privacy into a powerful personal AI tool.
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IBM watsonx Assistant
IBM watsonx Assistant is a next-gen conversational AI solution—it that empowers a broader audience that includes non-technical business users, anyone in your organization to effortlessly build generative AI Assistants that deliver frictionless self-service experiences to customers across any device or channel, help boost employee productivity, and scale across your business.
-User-friendly interface with drag-and-drop conversation builder and pre-built templates.
-Out-of-the-box Large Language Models, Large Speech Models, Natural Language Processing and Understanding (NLP, NLU), and Intelligent Context Gathering, to better understand the context of each conversation in natural language.
-Retrieval-augmented generation (RAG) for accurate, contextual, and up-to-date conversational answers around the clock, grounded in your company's knowledge base.
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