Development of a recommendation system for diet planning using artificial intelligence

Auto-notification system for inventory replenishment analytics. On 8n8. Small automation for e-commerce. Once a day, the system calculates the sales velocity for each product and sends a message in Telegram indicating when to reorder (with the recommended quantity) and how many days the remaining stock will last. What we do: Data retrieval: KeyCRM API (order history) + stock/orders from Rozetka (API or export) Storage in SQLite on my VPS (Contabo, Linux) Calculation of average sales, days of stock, reorder point ABC analysis: prioritization of which product to replenish first (class A — main by revenue — more important) Daily Telegram bot + cron job All thresholds (lead time, safety stock, target stock) — in the config

AI Automation Engineer / AI Marketing Automation Specialist Required About the Project I am looking for a specialist to create an automated social media management system for the company (Instagram and Facebook) using modern AI tools. The goal of the project is to maximize the automation of content creation processes, publication, result analysis, and partially communication with clients. Important: I am interested not in a one-time setup of publications, but in building a unified system that can be scaled in the future. What Needs to Be Implemented 1. System Design Develop the architecture for automation, select optimal services, and propose the best technology stack. 2. AI Integration Set up the use of ChatGPT for: generating a content plan; writing posts; creating texts for Stories and Reels; generating prompts for images; analyzing statistics; preparing weekly reports. Provide for the possibility of using Claude for strategic tasks: marketing strategy; competitor analysis; brand development; long-term planning. 3. Process Automation Set up automated scenarios (preferably Make or n8n) that can: initiate content creation; save materials; prepare publications; transfer them to Meta Business Suite; collect analytics; generate reports. 4. Meta Set up proper operation with: Instagram Business; Facebook Page; Meta Business Suite. Publications should be released simultaneously on Instagram and Facebook through Meta's official tools. 5. Analytics Organize automatic data collection on: reach; engagement; saves; comments; audience growth. Based on this data, AI should generate recommendations. 6. Documentation After the project is completed, provide: a description of the architecture; operating instructions; the ability for further independent support of the system. What I Would Like to See in the Contractor Experience with the following will be an advantage: OpenAI (ChatGPT); Claude; Make.com; n8n; Meta API; marketing automation; AI Agents; integrations between services. Please Indicate in Your Response What similar projects you have already implemented. What technologies you propose to use. What architecture you would recommend. Estimated cost and timeline for implementation. Examples of your work (if available). I am considering long-term cooperation. After a successful launch, further tasks for system development and the implementation of new AI tools may be possible.

A system is needed for the automatic processing of large volumes of information using AI. I am currently using my own prompt in Claude. It works well with small texts, but with larger volumes, the neural network may skip parts, stop before the end, or report completion even though the material has not been fully processed. A system is needed that can accept a book of 200+ pages, several books, PDFs, DOCX, TXT, subtitles, transcripts of audio and video, or another large array of information and automatically process it from start to finish. One of the main formats for the result for each meaningful sentence: English version. •••••••••••••••••••••••••••• Russian version. •••••••••••••••••••••••••••• English version. •••••••••••••••••••••••••••• English version. •••••••••••••••••••••••••••• Russian version. •••••••••••••••••••••••••••• English version. Each meaningful line is output four times in English and two times in Russian in the specified order. The translation must accurately convey the meaning. Short sentences can be combined, and long ones can be divided into complete meaningful lines. The format must be customizable: the number of English repetitions and translations, their order, languages, separator, line length, main prompt, and saving different templates. For example, instead of English–Russian–English–English–Russian–English, any other sequence can be chosen. If the document cannot be processed in one request, the program should automatically split it into internal blocks, send them to Claude, ChatGPT, Gemini, or another model, check the result, repeat problematic parts, and combine everything into one file. The user should not have to manually copy text for four pages. It is necessary to check that no sentence, paragraph, or meaningful fragment is missed, that there are no duplicates between blocks, and that the structure corresponds to the template. The check should not rely solely on the neural network's assertion. Audio processing The system should also process large archives of audio, such as a Telegram channel with 300 broadcasts of about one hour each. It is preferable to automatically download audio or accept the entire archive, recognize speech, and process everything without manual involvement. A structured summary should be created for each broadcast: topic, main thoughts, important facts, examples, recommendations, and conclusions. Greetings, advertisements, conversational filler, and meaningless repetitions are removed, but useful information is retained. After processing, not only separate notes are needed, but also one comprehensive readable document where the information is organized by topics. If a topic was discussed in different broadcasts, the materials are gathered into one section, duplicates are removed, and links to the original recordings are preserved. The results should include: — a summary for each broadcast; — a general thematic document; — search by words and topics; — connection of conclusions with the original audio; — saving progress and continuing after errors. I can already perform most of these actions myself, but only on a small scale and manually. Therefore, I am also open to considering a more efficient way to download and convert audio to text if the contractor offers a solution better than what I currently use. What to include in the response Please write: — how the system will be implemented and what product I will receive; — which AI and speech recognition models will be used; — how completeness is checked and how omissions and repetitions are excluded; — whether prompts, the number of translations, repetitions, and their order can be changed; — whether it is possible to download materials from Telegram; — the cost of development, API, timelines, and the price for further improvements. The main goal is a universal system that processes large books and hundreds of hours of audio without manual involvement, does not lose information, and delivers a finished result strictly according to the chosen template.

We're looking for an experienced Blockchain Full-Stack Developer to help build a next-generation Endless Runner Web3 game with on-chain gameplay mechanics, NFTs, and tokenized rewards. This is an opportunity to work on an innovative game that combines modern web technologies with blockchain infrastructure. You'll collaborate with game developers, backend engineers, and designers to build scalable smart contracts, Web3 integrations, and a seamless player experience.

We specialize in obtaining grants for existing companies that plan investments. We came up with the idea of creating/connecting available AI models to search for companies that are planning or are already in the process of investing and to offer them grants for this purpose (we mainly deal with grants for the purchase of machinery and equipment). The AI would search available websites and registries to find investors. Then, it would also handle the automation of mailing to these companies and would filter out companies that: - fit into the lead categories (I think, 5-6 parameters); - replied to the email and are interested in the grant; Of course, additional suggestions are welcome; I am also considering Voice Calling and SMS sending. I would like to emphasize that I am not only interested in finding LARGE or very LARGE companies, but also smaller ones, for example, employing 8-50 people. And not just large cities, but also smaller towns. Sample target for testing: SUBCARPATHIAN For micro, small, and medium-sized enterprises (SMEs) and large enterprises from the Subcarpathian Voivodeship that belong to the security and defense industry. An enterprise from the security and defense industry is understood as an enterprise that: develops or manufactures products, technologies, or systems intended for military applications, related to national security, critical infrastructure protection, or citizen safety or provides services supporting security and defense systems (e.g., in the field of cybersecurity) or conducts research and development in the area of military technologies and security systems and which achieves a significant share of revenue from the sale of products, technologies, systems, or services in the area of security and defense, i.e., above 5% of total net revenue (cumulatively over the last 3 closed accounting periods). Support available for companies that conduct business in an organized and continuous manner in the Subcarpathian Voivodeship for a period of no less than 24 months counting back from the date of the call for applications. We have proposals for websites to search. Ultimately, the program would prepare a daily summary of such investors for us. Can someone help us with this? I read that it is possible, but I don't have time to deal with it myself :)