Asteroid AI
Asteroid is an AI-driven browser-automation platform that lets both non-technical users and engineers build, deploy, monitor, and refine complex web workflows without writing traditional code. Its core is a graph-based agent builder where you describe desired tasks in natural language and configure repeatable logic with variables and structured outputs. Behind the scenes, Asteroid combines encrypted credential management, selector-based guardrails powered by Playwright, and live browser control to navigate pages, interact with UI elements, and call external APIs as needed. You can instantly deploy agents via a RESTful API, embed them into existing systems, or iterate in the platform’s console with real-time supervision, debugging tools, and human-in-the-loop checkpoints. Use cases range from multi-step data retrieval (insurance quotes, grant applications) and intelligent data entry into legacy systems (patient records, supplier portals) to automated reporting.
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Cognigy.AI
NiCE Cognigy delivers AI that works – fast, human, and built for real-world scale. As part of NiCE, a global leader in customer experience technology, we combine Generative and Conversational AI with orchestration, tools, and enterprise integrations to power Agentic AI.
The result? Smarter automation, better service, and instant resolution across every channel.
NiCE Cognigy’s AI Agents Supercharge Your Customer Service
-Industry-specific pre-trained AI Agents
-Multilingual call and chat support (100+ languages)
-Seamless integration with existing enterprise systems
-Leverages memory and context for hyper-personalized interactions
-Absorbs enterprise knowledge to accurately answer any customer query
-Real-time assistance and actionable service insights for human agents
Business Impact for our Customers:
-30% CSAT improvement
-70% AHT reduction
-99.5% Faster response time
-99% Routing accuracy
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Microsoft Agent Framework
Microsoft Agent Framework is an open source SDK and runtime designed to help developers build, orchestrate, and deploy AI agents and multi-agent workflows using languages such as .NET and Python. It combines the simple agent abstractions of AutoGen with the enterprise-grade capabilities of Semantic Kernel, including session-based state management, type safety, middleware, telemetry, and broad model and embedding support, creating a unified platform for both experimentation and production use. It introduces graph-based workflows that give developers explicit control over how multiple agents interact, execute tasks, and coordinate complex processes, enabling structured orchestration across sequential, concurrent, or branching scenarios. It supports long-running and human-in-the-loop workflows through robust state management, allowing agents to maintain context, reason through multi-step problems, and operate continuously over time.
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TEN
TEN (Transformative Extensions Network) is an open source framework designed to empower developers to build real-time multimodal AI agents capable of voice, video, text, image, and data-stream interaction with ultra-low latency. It includes a full ecosystem, TEN Turn Detection, TEN Agent, and TMAN Designer, allowing developers to rapidly assemble human-like, responsive agents that can see, speak, hear, and interact. With support for languages like Python, C++, and Go, it offers flexible deployment on both edge and cloud environments. Using components like graph-based workflow design, drag-and-drop UI (via TMAN Designer), and reusable extensions such as real-time avatars, RAG (Retrieval-Augmented Generation), and image generation, TEN enables highly customizable, scalable agent development with minimal code.
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