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  • Rating 561

Budget: 10000 PLN Deadline: 7 days

Vitaliy, the task is complex but solvable: I can deploy an autonomous AI agent on Windows with auto-start, memory, RAG, and browser/system management. I have worked with web services and automation, so I can assemble a combination of LLM, vector database, workflow, and management interface, as well as set up security and backups. After delivery, I will provide clear instructions and assist with initial testing. I am ready to discuss the architecture for your scenarios.

Advertising exchange in Telegram Vortex (Vue.js + Laravel)
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  • Rating 1 046

Budget: 1000 PLN Deadline: 10 days

Vitalik, hello

I will develop everything you wish and even more, I am free for work.
I can start everything today.

Preliminary consultation 2500 UAH.

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  • Rating 230

Budget: 1700 PLN Deadline: 5 days

Hello.

I carefully studied the technical specifications. Essentially, this is not just about simple configuration of Claude or Ollama, but about building a full-fledged autonomous AI system with memory, RAG, browser management, access to Windows, and the ability to execute scripts independently.

For the past few years, I have been developing AI solutions, automating business processes, and integrating LLM models into real working environments. I have worked with Ollama, Qwen, DeepSeek, Llama, LangGraph, CrewAI, ChromaDB, Qdrant, Playwright, Selenium, Open Interpreter, and automation systems on Windows.

What I can implement within your specifications:

✔ Deployment and configuration of a remote Windows server;
✔ Installation and configuration of Ollama with local models;

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  • Rating 328

Budget: 9999 PLN Deadline: 30 days

Hello.

Your project interests me. I can help with the development of an autonomous AI agent for a remote Windows PC with the ability to work with materials, a browser, files, applications, and execute specified scenarios.

I would like to note that such a system is better built in stages: first a secure MVP with a limited set of tasks and action control, then expanding autonomy after testing. This is important for stable operation 24/7 and protection against erroneous or undesirable actions of the agent.

Before providing an accurate estimate, I need to clarify:

— what specific tasks the agent should perform first;
— which websites, services, and applications it should use;

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  • Rating 308

Budget: 1000 PLN Deadline: 10 days

Hello, Vitaly!

I already have a similar autonomous agent working for myself, so most of the points in your technical specification are already implemented — I can show it on the finished product.

What has already been done and works:

- Autonomous 24/7 with auto-start after reboot (Windows Scheduled Task — I work on Windows, no need to port from Linux);
- Ingestion of materials: PDF, text, YouTube → transcription via Whisper → summary → stored in the agent's memory;
- Browser control using Playwright, plus a Telegram bot and a web dashboard for logs and management.

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  • Rating 457

Budget: 1000 PLN Deadline: 3 days

Good day! We can assist with deploying a standalone AI agent on a remote Windows PC / Windows Server. The project is clear: it is necessary not just to install the model, but to build a functioning agent system with memory, RAG, browser automation, access to the Windows environment, and the ability to perform tasks 24/7. We can implement:
— configuration of remote Windows PC / RDP
— installation of Ollama and local models
— building AI-agent workflow through LangGraph / CrewAI
— long-term memory through ChromaDB / Qdrant
— RAG pipeline for PDFs, texts, courses, and videos
— browser automation through Playwright / Selenium
— desktop automation through PyAutoGUI / Windows tools
— auto-start after reboot
— Telegram / web interface for agent management

  • Projects 5
  • Rating 4.2
  • Rating 690

Budget: 3600 PLN Deadline: 12 days

Hello, write to me in private messages and we will discuss all the details, but as colleagues mentioned, it's better on Linux, but we will figure something out.

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  • Rating 284

Budget: 4000 PLN Deadline: 9 days

Your Technical Assignment is composed very competently. The task of deploying a standalone OS/Browser-Use AI agent 24/7 on a remote Windows system is fully understood by us. At Lumvex studio, we specialize in complex AI integrations, the development of AI agents, and automation pipelines.

We understand the key pitfalls of such systems (for example, the loss of GUI context in Windows when closing the RDP session, VRAM requirements for local LLMs, and RAG memory synchronization in LangGraph).

Our technical solution for your points:
Remote PC Infrastructure:

We will select and configure a dedicated server (we recommend Hetzner / AWS with GPU, such as NVIDIA RTX 3090/4090 or A10G for comfortable operation of models with 14B/32B parameters).

We will set up a virtual display (Virtual Display Driver) so that when disconnected from RDP, the agent's screen does not "disappear" and GUI automation (PyAutoGUI / Open Interpreter) continues to see the Windows interface 24/7.

  • Projects 20
  • Rating -
  • Rating 2 116

Budget: 1000 PLN Deadline: 30 days

Good afternoon. I read the technical specifications — an autonomous AI agent is needed on a remote Windows server with long-term memory through RAG, browser and system management, an ingestion pipeline for PDF/MD/YouTube videos, and a Telegram control interface. Your stack choice is already close to optimal — I would like to make a few clarifications on the components based on my experience with similar setups.

Regarding the LLM engine: Ollama is a good choice for easy model deployment, but for long sessions with tool use, vLLM or llama.cpp server directly is more stable — Ollama can have unpredictable delays with large prompts. For models, if a GPU is available, Qwen2.5-Coder-32B or DeepSeek-Coder-V2 works well; on CPU only — Qwen2.5-7B-Instruct at most. For the agent framework, LangGraph is more convenient than CrewAI for long-lived agents because it has a clear state machine — this is critical for 24/7 operation and recovery after restarts.

Memory: I would choose Qdrant instead of ChromaDB for long-term storage — it scales better and has a decent hybrid search (dense + sparse). RAG pipeline on LlamaIndex plus custom ingestion handlers for each format: PDF through unstructured.io, YouTube through yt-dlp + Whisper, Markdown directly. I perform vectorization through sentence-transformers locally to avoid dependency on OpenAI embeddings.

Browser automation — Playwright is better than Selenium because it has built-in auto-wait and is much more reliable on dynamic content. Browser Use on top of Playwright works but adds instability — for production, I would prefer Playwright directly plus my own narrow API from tools.

System access: Open Interpreter is convenient for prototyping, but in a long-running agent, it’s better to provide a Python execution environment through RestrictedPython or Docker-in-Docker. PyAutoGUI should be kept for GUI operations, PowerShell for system commands via subprocess.

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  • Rating 379

Budget: 999 PLN Deadline: 3 days

Hello, Vitaly!
The task fully matches my profile: I have experience in creating autonomous AI agents, integrating LLM, and automating operating systems.
I am ready to implement the project "turnkey" based on the stack you proposed:
• Infrastructure: Deployment of Windows Server/Cloud PC with GPU, setting up 24/7 auto-start and stable RDP.
• Agent's brain: Local models (Qwen/DeepSeek/Llama) via Ollama + orchestration of logic on LangGraph / CrewAI.
• Memory (RAG): Storing knowledge in the vector database ChromaDB / Qdrant with a pipeline for processing PDF, text, and YouTube (Whisper).
• OS & Browser Automation: Using Browser Use / Playwright for web sessions and Open Interpreter / PyAutoGUI for full control of Windows (GUI, PowerShell, CMD).
• Interface: User-friendly Web UI or Telegram bot for monitoring logs, managing memory, and launching scripts.
I will ensure the security of command execution, set up backups, and provide you with a fully ready, tested system with step-by-step instructions.
I would be happy to discuss the details, architecture of the solution, and timelines in a call or chat.

SaaS platform for online art auctions with CRM and bidding system
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  • Rating 232

Budget: 1000 PLN Deadline: 7 days

I worked on UVWeb (https://ou-uv.com) — a B2B system on Flask/Python with automated data flows, REST API integrations, and event-driven logic for CodeZero Group.

I read the entire project brief. I understand the scope: Windows VPS + local LLM (Ollama/Qwen/DeepSeek) + vector memory (Qdrant/ChromaDB) + Playwright for browser control + desktop automation (PyAutoGUI/Open Interpreter) + ingestion pipeline for PDF/video/YouTube + 24/7 scheduler with auto-restart. This is a complete MVP of an agency system, not a simple configuration.

What I will do:
- Setup Windows VPS + Remote Desktop + autostart services after restart
- Implement Ollama with the chosen model (Qwen2.5:7b or DeepSeek)
- LangGraph agent with long-term memory (Qdrant + RAG pipeline)
- Playwright — browser control, clicking, reading data, forms
- PyAutoGUI + Open Interpreter — full Windows GUI automation

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  • Rating 234

Budget: 1000 PLN Deadline: 5 days

Hello. I have experience deploying autonomous AI agents on Windows/VPS with Ollama, RAG (Qdrant/ChromaDB), LangGraph/CrewAI, browser automation (Playwright), and desktop automation (PyAutoGUI/Open Interpreter). We can deploy a system with 24/7 operation, memory layer, ingestion pipeline (PDF/YouTube/texts), management via web or Telegram, and auto-start on Windows Server. We are ready to discuss architecture, timelines, and budget after agreeing on the details of the technical specifications.

  • Projects 13
  • Rating 5.0
  • Rating 4 233

Budget: 1000 PLN Deadline: 10 days

Hello! I have experience with similar systems (Ollama / OpenAI + LangGraph + RAG + Playwright + Windows automation), including deployment on VPS and setting up 24/7 operation.

For the stack, I see a solution through Windows VPS + LLM (Ollama / Qwen / DeepSeek) + LangGraph + vector memory (Qdrant) + Playwright + PowerShell/UI automation. Plus a simple web or Telegram interface for management.

To accurately assess the implementation, I need to understand:
— whether there is already a Windows server or if one needs to be selected;
— what level of autonomy is acceptable;
— whether working with real accounts in the browser is necessary or not;
— what specific tasks the agent should perform first.

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  • Rating 121

Budget: 1000 PLN Deadline: 1 day

Good afternoon. I am ready to complete this project and have extensive experience in developing various applications.

  • Projects 9
  • Rating 5.0
  • Rating 726

Budget: 1000 PLN Deadline: 3 days

Hello! Your project looks very promising. I am ready to start working and complete it at the highest level.

  • Projects 7
  • Rating 5.0
  • Rating 1 562

Budget: 1000 PLN Deadline: 1 day

I will help today
I will help today
I will help today
I will help today
I will help today
I will help today

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  • Rating 442

Budget: 13000 PLN Deadline: 20 days

Ready to take on the project. The architecture and stack are clear: Ollama, LangGraph/CrewAI, RAG, vector DB, browser + desktop automation, ingestion pipeline, and autonomous workflows on Windows.

But to be honest right away: this is not a "simple agent setup," but a full-fledged MVP of an autonomous AI system with infrastructure, memory, automation, and 24/7 operation.

Regarding timelines:

A working MVP/prototype of this level — approximately 2-3 weeks (14-20 days)
A fully stable system with recovery, security, proper memory, ingestion pipeline, monitoring, and resilient workflows — about 1-2 months.

Regarding budget:

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