Create an AI agent

Technical specification (full functionality described) Project AI Sales Agent for automatic search of potential clients, personalized email distribution, and lead processing. The initial business for which the AI Agent is being developed is intended for the project "platform for builders and construction equipment in Germany and the EU. Website: https://prostobau.de/ The goal is to create a fully autonomous system that can operate almost without my involvement and easily switch to any other business niche if necessary. Overall architecture The system should be modular. Each module should operate independently. For example: company search; website analysis; email search; letter generation; sending; response processing; reports. If it is necessary to replace Apify or OpenAI with another service, this should happen without rewriting the entire system. Company search sources At the first stage, use: Google Maps via Apify. In the future, there should be an easy way to connect: LinkedIn; Facebook; Gelbe Seiten; Yelp; any other sources. Company search Every day, the system automatically retrieves about 100 new companies based on the specified search query. For example: Baumaschinenvermietung Bayern Bauunternehmen Nürnberg Trockenbau München The search should be fully customizable. I should be able to change: niche; country; region; language; search queries; number of companies. Without the help of a programmer. Duplicate check Before processing, the company is checked by: domain; email; phone; Google Maps URL; name. A company should never receive the first letter twice. Website analysis If a website is found, the agent must: study what the company does; what services it provides; what products it sells; operating region; contact details; possible owner name; email. After analysis, create a brief description of the company. Email search Priority: personal work addresses → sales → vertrieb → kontakt → info. If there is no email — skip the company. Letter generation Via OpenAI. Each letter must be unique. Do not use template-based word replacement. The letter should consider the content of the website. Style: brief friendly professional without pressure without fabricated facts maximum 120 words. Letter check Before sending, the letter must be automatically checked. If errors are found: mistakes; fabricated information; too long text; poor personalization, the letter must be recreated. Sending letters Do not use the project's corporate email. Create a separate new domain for outbound email. For example, a separate similar domain. Create new mailboxes. Set up: SPF DKIM DMARC It is essential to organize proper email warming. After warming, aim for about 100 new emails per day. Emails should be sent gradually throughout the working day. Not all at once. Follow-up After 5 days from the first letter. Only if: no response; no bounce; the company did not request to stop writing. Only one follow-up. After the second letter, the chain ends. Response processing The system must automatically: read incoming letters. Determine: interested; not interested; request to stop writing; automatic response; vacation; manual response needed. After a response, automatically stop any further letters. Database Store: companies; websites; emails; letter history; responses; statuses; search queries; errors; processing date; follow-up. Dashboard A convenient web interface (desktop) is needed, not just n8n. I want to see: Main is the agent working; current status; how many companies found; how many processed; how many sent; how many responses; how many errors; how many follow-ups; how many interested. Companies Table. Filters. Search. History. Search queries Add Delete Edit Priority Region Country Number of companies. Settings Without a programmer, the following should be changeable: OpenAI model; email account; domain; number of letters; limits; language; template; sending time; number of companies; follow-up period; business niche. Logs All errors. All actions. Work history. Emergency stop Large button STOP After pressing: immediately stop search; generation; sending; follow-up. Restart With one button. Operating modes Test Everything is executed except sending. You can check letters. Automatic Fully autonomous operation. Scaling In the future, there should be the ability to: add multiple email accounts; multiple domains; multiple projects; multiple niches; multiple countries; multiple languages. Without a complete system overhaul. Daily report (organize conveniently, either by email to the owner or in Telegram via a bot) At the end of the day, automatically receive: companies found; new; duplicates; emails found; letters sent; follow-ups; responses; interested; errors. Security Store all API keys securely. No keys inside the workflow. Documentation After project completion, provide: launch instruction; settings change instruction; architecture description; export of all workflows; access to all services. Important The project should be built not only for ProstoBau. I want to receive a universal platform for client search that can be used in the future for almost any business by simply changing: niche; search queries; letter templates; email; domain; country. Without involving a programmer.

We are looking for a specialist or a team to implement AI solutions in the communication of the CT and MRI medical center. Requirements: integrate AI into telephony for handling incoming and cold calls; ensure natural Ukrainian-speaking communication with minimal pauses; integrate an AI assistant into the Binotel chat or propose an effective alternative; automate responses to inquiries, initial consultations, and scheduling for examinations. Important: the medical field requires accurate information gathering before CT or MRI, particularly regarding the examination area, preparation, referrals, and possible contraindications. The solution must be empathetic, professional, and allow for the transfer of complex cases to an operator. In your response, please send relevant cases, a description of the proposed solution, and estimated timelines. Experience in medical projects will be an advantage.

It is necessary to develop an application in MATLAB that can process images/videos, identify individual objects, analyze their characteristics, and, if necessary, use machine learning methods to automate the analysis. Desirable: confident knowledge of MATLAB; experience in Computer Vision / Image Processing; experience with Machine Learning;

Developer for creating AI bots - multi-agent system and automations in AI application. What is needed: proficiency in n8n; experience integrating OpenAI and other AI models via API; working with webhooks, REST API, and Supabase; ability to create reliable AI workflows and automations. Create multi-agent systems from scratch or with a framework AI Agents, MCP, RAG

Counting of finished products and peopleNon-conforming products. Based on a high-performance line, ensure accurate counting of throughput, workforce participation, identification of non-conformities, and context of stops/reconfigurations, providing ready analytical information.