Ivan Trushkov is a Prompt Engineer and Vibe-Coder with a strong management background and deep expertise in business processes. Over the course of 10 years in management and operational system development, he has implemented end-to-end accounting and automation in three major companies, focusing on process diagnostics, data model design, integrations, regulations, metrics, and quality control.

Ivan specializes in applied AI, developing RAG architectures, neural collaborators, advanced chatbots, and task chain automation through n8n/Albato, often utilizing Telegram as the frontend. He excels at translating requests into clear architectural solutions, bringing them to production with monitoring and quality control in place.

Reviews

Ivan Trushkov is a reliable and punctual client, known for prompt payments, clear and well-structured technical specifications, quick feedback, and friendly communication. All reviews highlight his responsibility, reasonable deadlines, and positive attitude towards collaboration. No negative comments have been reported.

Portfolio projects

Skills and Technologies: Algorithmic generation, document processing, artificial intelligence, Google AI Studio, Google Gemini AI, OpenAI, GigaChat, RBAC, web development, Telegram bots.

Projects and Achievements: Ivan has developed several innovative tools, including SheetMetalGen AI, which automates the creation of DXF and PDF drawings for facade cassettes, significantly speeding up documentation preparation and reducing the risk of errors. Atlas AI, a corporate AI assistant, enhances access to information within the company, providing quick and accurate responses based on internal documents. GenPresent AI helps businesses and teams quickly create high-quality presentations, saving time and standardizing formats.

Achievements and Recognition: Ivan's projects demonstrate significant improvements in task speed and quality, such as accelerating production launches, enhancing response quality, and reducing errors in operational activities. These tools contribute to the standardization and simplification of processes, as evidenced by their successful integration into users' workflows.

* It is created by a neural network based on a portfolio, information provided by the user about himself and reviews from other users.

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