AI Agents

Hello, Ivan.

I read the task — it is generally clear, but for an accurate assessment, I need 5 answers. They will determine the architecture, the volume of work, and the deadlines:

1. Through which channels does the agent reach the manufacturer — email, LinkedIn, WhatsApp, forms on websites? Or a combination?
2. In which languages is the correspondence conducted (English, Ukrainian, others)?
3. Volume — how many leads are planned to be processed per month?
4. Are we looking for manufacturers from scratch (parsing LinkedIn / Google Maps / industry directories) or is there already a database of contacts?
5. Is the "contract" at the end a fixation of the terms in the correspondence itself, a commercial proposal, or a full legal document?
…
The stack for such a task: LangGraph + OpenAI/Claude for the dialogue logic of agents, n8n for orchestrating channels, Google Sheets or Airtable as CRM for leads and correspondence history.

Preliminarily — we are within the specified 26,000 UAH / 21 days with a basic configuration (1-2 communication channels, one language of correspondence). After receiving answers to the questions above, I will return with an accurate assessment and a plan for the stages.

I am waiting for your answers.

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Good day!
I have experience in developing AI agents and automated scenarios, where it is necessary not just to generate a response, but to build a coherent logic of search, communication, and bringing the process to a specific result.
This involves a connection of agents: searching for a suitable product, contacting the manufacturer, conducting correspondence, collecting prices and terms, and then bringing it to the stage of agreements or contract signing. Here, it is important to correctly establish the roles of the agents, the logic of context transfer, and control at each stage.
I suggest discussing the details, as well as the cost and timelines in private messages.

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Hello!
I can implement a connection of such agents through the n8n service. I have extensive experience in implementing AI agents.

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Hello.
I see this as an agent connection: product/manufacturer search → message generation → correspondence management → price and terms collection.
I can implement the MVP and then refine it according to your process.

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Hello, nice to meet you.

I am confident that I can help you develop and create a multi-agent artificial intelligence system that automates the workflows of product searching, communication with suppliers, and negotiations up to obtaining prices and commercial terms.

I have worked on automation systems that combine LLM agents, API integrations, and workflow orchestration for lead generation, supplier searching, and business process automation.

I will start by developing the agent architecture (research agent → qualification agent → communication agent → negotiation/conversation agent), including a clear role distribution and state management. Next, I will implement the product search logic (web scraping/API), supplier identification, and automated outreach via email or messaging channels with structured prompts and safeguards. Finally, I will create conversation tracking, response analysis, and a dashboard/log system so you can monitor negotiations, extract prices, and approve next steps.

I take pride in creating managed AI agent systems that are reliable, traceable, and secure for real business communication, rather than experimental prototypes.
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Relevant experience:

- Multi-agent workflow systems for lead generation and customer relationship automation
- Business automation based on LLM (email matching + supplier searching channels)
- Hybrid API + parsing systems with structured data extraction and logging

Let’s define your target product sources, communication channels, and matching rules so I can develop a stable agent workflow.

Looking forward to collaborating,

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Hello! I have reviewed your project and am ready to start working. I can guarantee excellent results in a short time.

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We can implement your project to create a connected system of AI agents that will find products, reach out to manufacturers, and negotiate to obtain prices and terms of cooperation. Our experience in developing complex automated systems, integrating with APIs, processing data, and building business logic allows us to execute such a case effectively and at scale.

We propose using Python (FastAPI) for the backend, LLM agents with memory and dialogue history, tools for web scraping (such as Playwright or Scrapy) for product searches, as well as mechanisms for automating correspondence (email, messengers, forms). Everything will operate on a reliable server with monitoring and logging.

We have experience in creating similar solutions for automating procurement and B2B communications. We are ready to discuss the details — the structure of the agents, sources for searching, mechanisms for verifying manufacturers, and the format of data output.

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