Comprehensive scalable AI agents Tools for Every Need

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scalable AI agents

  • Grow your AI Voice Agency with Vapify's White-Label Platform.
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    What is Vapify?
    Vapify provides an AI voice white-label platform designed to increase your brand's credibility and revenue. Easily integrate your current Vapi setups with Vapify, ensuring enhanced functionality and brand recognition. With extensive experience and deep understanding of Vapi's voice AI, Vapify offers a branded solution that improves client relations without revealing Vapi. Customizable and scalable, Vapify allows you to tailor the look and feel of your AI voice agents to match your brand, ensuring your business grows without the burden of additional overhead.
  • GreyCollar is an AI agent platform that automates business processes by creating intelligent digital workers capable of task orchestration.
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    What is GreyCollar AI?
    GreyCollar AI enables organizations to design, train, and deploy AI-powered digital workers through a user-friendly, no-code interface. By ingesting documents, knowledge bases, and APIs, these agents understand company protocols and workflows. They seamlessly integrate with communication platforms like Slack and Microsoft Teams, handling tasks such as answering FAQs, processing IT tickets, and routing service requests. Built-in memory systems allow agents to recall past interactions, ensuring coherent and personalized responses. Administrators can monitor performance metrics, adjust workflows, and scale agents across teams. Whether improving customer service, streamlining HR onboarding, or automating sales outreach, GreyCollar AI transforms manual processes into efficient, automated workflows that drive productivity and reduce operational costs.
  • MCP Agent orchestrates AI models, tools, and plugins to automate tasks and enable dynamic conversational workflows across applications.
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    What is MCP Agent?
    MCP Agent provides a robust foundation for building intelligent AI-driven assistants by offering modular components for integrating language models, custom tools, and data sources. Its core functionalities include dynamic tool invocation based on user intents, context-aware memory management for long-term conversations, and a flexible plugin system that simplifies extending capabilities. Developers can define pipelines to process inputs, trigger external APIs, and manage asynchronous workflows, all while maintaining transparent logs and metrics. With support for popular LLMs, configurable templates, and role-based access controls, MCP Agent streamlines the deployment of scalable, maintainable AI agents in production environments. Whether for customer support chatbots, RPA bots, or research assistants, MCP Agent accelerates development cycles and ensures consistent performance across use cases.
  • ADK-Golang empowers Go developers to build AI-driven agents with integrated tools, memory management, and prompt orchestration.
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    What is ADK-Golang?
    ADK-Golang is an open-source Agent Development Kit for the Go ecosystem. It provides a modular framework to register and manage tools (APIs, databases, external services), build dynamic prompt templates, and maintain conversation memory for multi-turn interactions. With built-in orchestration patterns and logging support, developers can easily configure, test, and deploy AI agents that perform tasks such as data retrieval, automated workflows, and contextual chat. ADK-Golang abstracts low-level API calls and streamlines end-to-end agent lifecycles—from initialization and planning to execution and response handling—entirely in Go.
  • An extensible Node.js framework for building autonomous AI agents with MongoDB-backed memory and tool integration.
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    What is Agentic Framework?
    Agentic Framework is a versatile, open-source framework designed to streamline the creation of autonomous AI agents that leverage large language models and MongoDB. It equips developers with modular components for managing agent memory, defining toolsets, orchestrating multi-step workflows, and templating prompts. The integrated MongoDB-backed memory store enables agents to maintain persistent context across sessions, while pluggable tool interfaces allow seamless interaction with external APIs and data sources. Built on Node.js, the framework includes logging, monitoring hooks, and deployment examples to rapidly prototype and scale intelligent agents. With customizable configuration, developers can tailor agents for tasks such as knowledge retrieval, automated customer support, data analysis, and process automation, reducing development overhead and accelerating time-to-production.
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