Multi-Agent Task Automation Framework

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@Appworldz

Hey, Sahanaj here. This is exactly the kind of orchestration work I have been doing recently with Microsoft Copilot Studio, Azure OpenAI, Power Automate, Claude, and multi agent workflow systems. I have built chained AI agent environments where specialized agents handled document intake, email triage, scheduling, approval routing, data extraction, and operational task delegation autonomously across both browser and desktop connected environments. Most of the complexity usually comes from state management, context passing, and reliable inter agent communication, not the prompts themselves. Your Microsoft focused stack is a strong choice because SharePoint, Teams, Power Automate, Azure AI, and Copilot can work together very effectively when the orchestration layer is designed properly. The current budget is low for a 16 agent orchestration system with hybrid execution and enterprise workflow integration. A more realistic starting budget is around 80,000 to 200,000 INR depending on orchestration depth and autonomy requirements. I can start immediately and iterate rapidly with staged demos and workflow validation.

@SmartCodeDev

Hello, I have experience building multi agent AI automation systems using Microsoft toolchains including Power Automate Azure OpenAI M365 Copilot SharePoint Teams and Claude based workflows. I can help architect and orchestrate your 16 agent system with reliable communication between browser based and desktop based agents using APIs local services queues and event driven workflows. My background includes autonomous task automation for email triage document processing scheduling CRM updates and chained business workflows where agents collaborate and hand off tasks without manual intervention. I am comfortable working with hybrid environments integrating Microsoft services document intelligence semantic search and custom orchestration layers through Python Node.js and Azure services. I can start immediately review the specification document and iterate quickly toward a working orchestration demo and scalable production architecture.

@KarthikTechCon

Hi, Your multi-agent automation framework is exactly the kind of complex orchestration work I enjoy building. I have 15+ years of experience in enterprise automation, distributed systems, and AI-integrated workflow platforms, including Microsoft ecosystems and agent-based architectures. I’m comfortable working across: ✔ Power Automate ✔ Azure OpenAI & AI Search ✔ M365 Copilot ✔ SharePoint & Teams integrations ✔ VS Code extension workflows ✔ Claude/OpenAI multi-agent coordination ✔ Desktop + browser hybrid automation What stands out in your requirement is the orchestration layer between 16 specialized agents and maintaining reliable communication across browser and desktop environments. I can help design a scalable architecture using queues/events, API gateways, shared memory/context handling, and agent-to-agent task routing with proper monitoring and retry logic. I’ve previously worked on automation systems involving: • Email triage & response workflows • Intelligent scheduling pipelines • Autonomous document/data processing • Multi-step business process automation • Human-in-the-loop approval systems My focus will be: • Stable orchestration • Fast iteration cycles • Maintainable architecture • Secure enterprise-grade integrations I can start immediately and would be happy to review the specification document and propose the best orchestration strategy for the first working demo. — Karthik

@Shrutibimpl

Hello, I am a technology leader and developer specializing in scalable AI/ML automation, native background services, and complex systems integration. I am ideally equipped to deliver this multi-agent network. Why me? I have deep expertise orchestrating multi-agent networks. I specialize in routing tasks from a central supervisor agent to dedicated specialists to automate workflows seamlessly. My day to day stack perfectly mirrors your requirements, including Copilot Studio, Power Automate, Teams, SharePoint, Azure open ai, and Microsoft Search. I specialize in building hybrid, highscale architectures that bridge server side web APIs with native, client side desktop agents. Whether using a robust message bus or local processes, I ensure reliable, low latency, cross context communication. I build production systems that reason independently, manage tasks, and eliminate operational bottlenecks. I have couple of critical questions, lets discuss in details. Thanks, Bharat

@Microlent

This looks straightforward at first, but in my experience there’s usually a key detail that can cause issues later. I’ve handled similar projects before and can outline a practical approach for you. For similar work and case studies, feel free to check my profile: https://www.freelancer.com/u/Microlent Let me know if you I'd like me to walk you through the plan. – Rajesh Rolen

@KrisuTechkul

Hi, we are a team of 20+ AI/ML Engineers based in Delhi - have completed 300+ projects with 100% client satisfaction & long term association. As we embark on building your Multi-Agent Task Automation Framework, my team and I bring to the table extensive skills and experience in Artificial Intelligence (AI) development with a particular focus on creating innovative frameworks. Our expertise extends to machine learning, deep learning, robotic process automation, and neural networks -- all crucial elements for effective agent orchestration at scale. With a track record of delivering tailor-made AI solutions for complex business challenges, we are well-versed in leveraging cloud-based AI to ensure precision, efficiency, and measurable results - paramount for your hybrid environment. Moreover, our experience working with diverse data streams including web APIs and local processes will prove invaluable in enabling smooth communication between your agents living within the browser-based workspace and desktop clients. We have tackled similar complex workflows before such as data entry handling, email triage, scheduling - all which aligns perfectly with your project's core requirements.

@jaroslavcaprata

The difficult part of multi-agent systems is rarely generating responses — it’s maintaining reliable orchestration, state management, and recovery when workflows span browser environments, desktop processes, APIs, and human-facing systems like M365. For a 16-agent setup, I’d avoid tightly coupled “chatting agents” and instead structure the system around explicit task contracts, shared memory/state, and controlled handoff logic. That keeps workflows deterministic enough for production automation while still allowing reasoning flexibility where it matters. Your Microsoft-heavy stack is well suited for this: * Power Automate for operational triggers/workflows, * Azure OpenAI + Claude for reasoning layers, * SharePoint/Search/Document Intelligence for retrieval and structured context, * Teams/M365 integration for human escalation and approvals. I’d likely implement orchestration through a central coordinator service with queue-based communication between agents, plus structured logging and retry handling so failures don’t silently break chains. Hybrid browser/desktop execution can be handled through lightweight local workers communicating over secured APIs or message channels. The first milestone should focus on a narrow but complete workflow — for example email triage → document extraction → scheduling/action routing — before scaling to all 16 agents. That usually exposes orchestration bottlenecks early and prevents the framework from becoming difficult to maintain later.

@webnsoftindia

Hi, I would worked with AI workflow automation and multi-agent systems, and your project around 16 AI agents with orchestration is something I can help with. I have experience with the Microsoft ecosystem including Power Automate, M365 Copilot, SharePoint, Teams, Azure OpenAI, Search, Document Intelligence, VS Code, along with integrating external AI models like Claude. For your setup, I can help build an orchestration layer where agents receive goals, reason through tasks, pass outputs between specialist agents, and complete workflows with minimal human intervention. I’m also comfortable handling hybrid environments where browser-based agents communicate with desktop processes using APIs, queues/message buses, and local integrations. Relevant workflow examples include: AI-driven data entry automation Email classification & response routing Scheduling and task coordination Multi-step document processing workflows Agent handoff systems with shared memory/context I can review the attached specifications, understand the orchestration logic for all 16 agents, and quickly move toward an initial demo so we can iterate fast. Ready to start immediately. Looking forward to discussing architecture and workflow details.

@dushyant317

With strong experience in AI agent orchestration, enterprise automation systems, Microsoft AI ecosystems, and multi-agent workflow architectures, we can help build a scalable orchestration layer where browser-based and desktop-based AI agents collaborate autonomously across chained business workflows.

@manoval09

I can't write a compelling proposal yet—the project brief is incomplete. I need: 1. **Full project description** (it cuts off at "we have 16 agents initially and...") 2. **The attached specifications document** (paste the content here) The current information isn't enough to: - Reference specific technical requirements (hard rule #1 in my brief) - Understand what these 16 agents actually do - Demonstrate relevant expertise with concrete technical choices - Suggest a realistic timeline or deliverables Once you provide the complete specs, I'll write a proposal that: - Opens with their actual pain point (specific detail from their brief) - Outlines a concrete technical approach - Includes one specific technical choice (library, pattern, architecture decision) - Drives commitment with a clear first-24-hours step Paste the full description and specs doc, and I'll have the proposal ready immediately.

@raiha2

Hi there, Orchestrating 16 agents across a hybrid (browser and desktop) environment requires a robust state management system and message bus. How I will resolve this using your stack: - Hybrid Orchestration: Connecting web-based agents to desktop clients using a low-latency local WebSocket message bus or a custom Python automation runner. - Microsoft Ecosystem: Seamlessly integrating SharePoint, Teams, and Azure Document Intelligence for automatic email triage, data entry, and file management. - Orchestration logic: Utilizing Azure OpenAI/Claude to power the reasoning loops, routing tasks dynamically between specialist agents. I have built complex, autonomous multi-agent pipelines before. Let’s jump on a quick chat to discuss the specific architecture outlined in your attached doc. Best regards, Raiha

@dholadipak09

Hello, I can help build your multi agent task automation framework with the initial 16 agents, orchestration flow, and hybrid communication between browser based workspace and desktop client. I understand this is not just a chatbot setup. The important part is designing agents that can receive goals, break work into steps, pass tasks to specialist agents, call the right tools, track state, handle failures, and complete repetitive workflows without constant human nudges. I can work with Microsoft Power Automate, VS Code, M365 Copilot, SharePoint, Teams, Azure OpenAI, Azure AI Search, Document Intelligence, Claude, Python, APIs, and local process automation. My approach would be to first review your specification document, define the agent roles and handoff rules, then build the orchestration layer, message flow, memory/state handling, tool connectors, browser and desktop communication bridge, and a first working demo around one real workflow such as data entry, email triage, document processing, or scheduling. After that, we can expand agent by agent in clear milestones. Best regards Ankit

@adityabhalsod007

Hi, Your project aligns perfectly with the type of AI automation systems I'm interested in building. I understand that this is not a simple chatbot implementation—you need a coordinated multi-agent ecosystem where 16+ agents can receive goals, reason through tasks, delegate work to specialized agents, exchange context, and complete workflows with minimal human intervention. My approach would be to first analyze the orchestration architecture, agent responsibilities, communication patterns, and failure-handling requirements from your specification document. From there, I would design a scalable framework using Microsoft's ecosystem (Power Automate, Azure OpenAI, M365 Copilot, SharePoint, Teams, Document Intelligence) while ensuring seamless communication between browser-based and desktop-resident agents through APIs, queues, webhooks, and local service connectors. I have experience building Python-based automation systems, integrating AI workflows, API orchestration, document processing, and business process automation. For a project of this complexity, my focus would be reliability, observability, context management, and agent-to-agent coordination rather than just generating responses. Looking forward to discussing the 16-agent design and implementation roadmap. Best regards, Aditya

@sjohn117

Hi,\n\nAs an AI & Full-Stack Developer with over 10 years of experience, I specialize in building scalable systems and have a strong background in task automation and agent orchestration. I understand you're looking to develop a Multi-Agent Task Automation Framework with a focus on enabling AI agents to collaboratively manage tasks without human intervention.\n\nIn my previous roles, I've successfully implemented agent systems that automate workflows in areas like data entry and email triage, ensuring seamless communication between web APIs and desktop clients. I share your vision of streamlining task workflows through intelligent orchestration of agents, utilizing tools like Microsoft Power Automate and Azure Open AI.\n\nMy approach emphasizes clean code, robust testing, and comprehensive documentation, ensuring the solutions are efficient and easy to maintain. I can deliver the initial demo within a week to kickstart our collaboration. What specific tasks do you envision the agents handling within the automation framework? \n\nThanks,\nSean

@Legend749

Hello, As a Full-Stack Developer and the Founder of ExamerAI, I regularly engineer complex asynchronous processing layers, API integrations, and automated workflows. I can help you architect a robust, autonomous multi-agent orchestration framework that seamlessly connects your hybrid environments. My technical approach to your 16-agent orchestration blueprint: • Hybrid Context Communication: To bridge your browser-based workspaces and desktop clients, I will wire together secure local process listeners and web APIs, utilizing a lightweight local message bus to ensure seamless, real-time message passing and multi-step data handoffs. • Autonomous Task Chaining: I will structure the reasoning and execution pipeline so each agent independently processes its assigned goal, formats the payload correctly, and triggers the next specialist agent without requiring human intervention. • Toolchain Familiarity: I am comfortable working with Python-based agent architectures and integrating with your required tools, including VS Code environments, Azure OpenAI APIs, Claude, and document intelligence workflows. I am ready to start immediately and focus on delivering a fast, functional initial demo. Let's connect over chat to review your attached specifications document! Best regards, Abhinav Raj

@mykolas67

Main challenge here is not building individual agents, but designing reliable orchestration so 16 agents can coordinate without conflicts, loops, or loss of task context across web + desktop environments. I would structure this as a central orchestrator (Python-based, event-driven) that assigns tasks to specialized agents with clearly defined inputs/outputs, rather than free-form autonomy. Each agent would act as a bounded service (planner, extractor, validator, email handler, scheduler, etc.), and communication would flow through a message bus (Azure Service Bus / Redis queue) to ensure traceability and retry safety. For Microsoft stack integration, I’d lean on Power Automate + Azure OpenAI + SharePoint connectors for enterprise data flow, with lightweight APIs bridging desktop and browser-based agents. I’ve worked on multi-step automation systems where reliability depended more on orchestration discipline and state tracking than on the models themselves. I can start by simplifying your 16-agent structure into a minimal working loop first, then scale it into full parallel orchestration once the workflow is stable. Thank you Mykola Sagin

@hugog17

⭐⭐⭐⭐⭐ Senior Multi-Agent AI Automation⭐⭐⭐⭐⭐ Hello there, I am an AI automation engineer specialising in multi-agent orchestration using Microsoft's toolchain — Azure OpenAI, Power Automate, M365 Copilot, and SharePoint — with Claude API integration for reasoning-heavy agent tasks. A 16-agent system where specialists hand work to each other without human nudges requires a reliable message bus and clear state handoff between agents — the most common failure point is agents losing context mid-chain when the orchestration layer doesn't persist intermediate results correctly between browser-based and desktop-based contexts. Built multi-agent automation frameworks using Azure OpenAI with Power Automate flows as the orchestration layer, SharePoint as the shared state store between agents, and Teams webhooks for loop-closing notifications. Email triage, document processing via Document Intelligence, and scheduling workflows running autonomously end-to-end without manual intervention. The hybrid browser/desktop communication is handled cleanly through Azure Service Bus or Power Automate HTTP connectors — keeping both contexts in sync without custom middleware. Could you share the specification document in chat so I can review the 16 agent roles and their orchestration flow before proposing the architecture?

@JoseRCarvas

Read through your specs on the 16-agent orchestration—especially the hybrid browser/desktop split. I built a similar system where Python agents communicated via Redis pub/sub: browser-based Playwright scrapers passed data to local Selenium bots for desktop form-filling, all coordinated by a single controller script that logged completion states. What's your current plan for error states when an agent stalls mid-task between the browser and desktop environments?