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  • AIFlow Guru is a low-code AI agent orchestration platform enabling visual creation of autonomous agent workflows integrating LLMs, databases, APIs.
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    What is AIFlow Guru?
    AIFlow Guru is a comprehensive AI agent orchestration platform that empowers developers, data scientists, and business analysts to build autonomous agent workflows using a visual flowchart-like interface. By connecting pre-built components such as prompt templates, LLM connectors (OpenAI, Anthropic, Cohere), retrieval tools, and custom logic blocks, users can compose complex pipelines that automate tasks like data extraction, summarization, classification, and decision support. The platform supports scheduling, parallel execution, error handling, and metrics dashboards for end-to-end visibility and scale. It abstracts away infrastructure details, supporting both cloud and on-prem deployments, ensuring security and compliance. AIFlow Guru accelerates AI adoption in enterprises by reducing development time and unlocking reusable workflows across teams.
  • Boxsy helps SaaS founders spend more time on the business, not in the business.
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    What is Boxsy?
    Boxsy is a comprehensive platform that reduces the operational burden for startup founders by providing essential tools, expertise, and insights. With features such as metrics dashboards, operational playbooks, automated reporting, and more, Boxsy helps SaaS founders break data silos, gain clarity on business health, and get tailored guidance from experts. The platform also offers software discounts and AI-powered tools to generate insights and automate tasks.
  • LLMStack is a managed platform to build, orchestrate and deploy production-grade AI applications with data and external APIs.
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    What is LLMStack?
    LLMStack enables developers and teams to turn language model projects into production-grade applications in minutes. It offers composable workflows for chaining prompts, vector store integrations for semantic search, and connectors to external APIs for data enrichment. Built-in job scheduling, real-time logging, metrics dashboards, and automated scaling ensure reliability and observability. Users can deploy AI apps via a one-click interface or API, while enforcing access controls, monitoring performance, and managing versions—all without handling servers or DevOps.
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