Vladyslav Petrychenko
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Khmelnitskyi,
Ukraine
15 days 9 hours back
available for hire
11 Safes completed
3 months 10 days back
7 clients
age 21 years
on the service 6 years
Rating
Language proficiency level
Українська: fluent
English: pre-intermediate
Русский: pre-intermediate
Skills and abilities
Programming
Services
Promotion
Administration
Outsourcing & consulting
Portfolio
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AI system for predicting customer risks (Risk & Sentiment A
AI & Machine Learning
Development of an intelligent system that automatically analyzes the tone of dialogues in the CRM system in real-time, allowing management to detect conflict situations before they become critical.
Challenge:
The client faced the problem of "unexpected" refusals and conflicts. Managers often did not manage to notice changes in the client's mood in correspondence in time, which led to "putting out fires" already at the stage of losing a deal. A tool was needed that could "see" tension in communication 24/7.
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My solution:
I designed a system that transforms each text in the dialogue into a risk assessment:
Data integration: Set up a continuous flow of data between the CRM system and the processing service via API (Make).
AI sentiment analysis: Implemented neural network analysis that evaluates each message on a scale of emotional coloring. The system assigns one of three statuses to the dialogue:
Green: Stable loyalty.
Yellow: First signs of dissatisfaction.
Red: High risk of conflict, immediate intervention required.
Preventive notification system: If the dialogue falls into the "Red" zone, the responsible manager or supervisor immediately receives a notification with an excerpt of the risk reason.
Technology stack:
Make (Integromat)
OpenAI / Claude (Sentiment Analysis API)
CRM Integration (API/Webhooks)
Notification Stack (Telegram/CRM Internal alerts)
Result:
Shift to strategy: The client replaced the reactive "firefighting" model with proactive relationship management.
Reduction of churn: Conflict situations are detected at early stages, allowing for the preservation of customer loyalty.
Transparency of communications: The manager sees the "temperature" of the sales department in real-time without having to read thousands of messages manually.
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Analytical AI Digest of Strategic Management
AI & Machine Learning
Development of a "cross-analytics" system that automatically consolidates data from various corporate sources, conducts intelligent processing using AI, and provides the manager with a concise daily report on the state of the business.
Challenge:
The company's management was forced to spend hours manually collecting reports from various CRMs, accounting systems, and marketing services. The process was fragmented, making it difficult to quickly identify risks and make strategic decisions.
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My solution:
I built a centralized automation and analytics system:
Data aggregation: I set up cross-integration (Make) to collect "raw" data from several independent systems via API.
Intelligent analysis (AI): Instead of simply copying numbers, I added a processing stage with an AI model (GPT/Claude). The AI analyzes the dynamics of indicators, compares them with planned values, and identifies potential risks or deviations.
Automated digest: I created logic that automatically generates a concise, structured report in Telegram every day at 08:00. It contains only the key figures and AI conclusions necessary for decision-making.
Technology stack:
Make (Integromat)
OpenAI API / Claude API (AI Intelligence)
REST API (Data fetching)
Telegram Bot API (Reporting)
Result:
Focus on the main: The manager receives a complete picture of the company's status in one message in 1 minute instead of hours of waiting for reports.
Proactivity: Thanks to AI risk assessment, the system highlights "red zones" that require immediate attention.
Efficiency: Complete abandonment of manual report preparation — the process has become autonomous and error-free.
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223 USD Case: Response Time Monitoring System (SLA Chat Analytic)
AI & Machine Learning
Building a real-time analytics system to monitor the speed of processing incoming requests in chats. The solution allowed the support team to significantly improve customer service metrics (SLA).
Challenge:
The client did not have an objective tool to track customer waiting time for a manager's response. This led to a "drop" in communication speed, customers left the chats, and management received delayed reports that did not reflect the actual performance of the department.
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My solution:
I developed the architecture for automated data collection and processing through the Make (Integromat) platform:
API Integration: Set up a continuous data transmission channel from the client's chat platform. Each new activity in the chat becomes a point for real-time analysis.
Mathematical Logic: Implemented scripts for automatically calculating the time from the moment a customer reaches out to the first response from a manager.
Multi-level Alert/Warning System: Configured threshold logic. If the waiting time approaches critical levels, the system automatically sends a warning, allowing the manager to intervene before the customer loses patience.
Performance Dashboard: All data is aggregated into reports that allow assessing the effectiveness of each manager individually and the department as a whole.
Technology Stack:
Make (Integromat)
Webhooks & API Integration
Google Sheets (Data processing & Storage)
Telegram/Email Notification System
Result:
Measurability of service: Management received transparent metrics of response speed (SLA) in real-time.
Increased response speed: Thanks to the alert system, the team began to respond to requests faster, minimizing customer churn.
Objective assessment: The system provided a basis for fair employee motivation based on their actual performance.
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178 USD Automation of the photo report monitoring system (Foto Control)
AI & Machine Learning
Development and implementation of an automated quality control system for projects that minimizes human factors and provides instant feedback on the status of reports.
Challenge:
The client faced the problem of untimely submission of photo reports from projects. Manual verification of data from closed corporate systems was ineffective, taking hours of managers' time and leading to overdue reports being identified too late.
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My solution:
I designed and integrated an automated monitoring system based on the Make (Integromat) platform:
API Integration: Set up a secure connection to the client's closed API system to extract raw data in real-time.
Data Processing: Created logic in Make for normalizing data, checking timestamps, and automatically filtering reports by status.
Visualization: Set up automatic export of processed data to Google Sheets, where the system automatically highlights overdue reports and sorts them by priority.
Notification System: Implemented a mechanism that allows the manager to instantly see projects that have fallen behind schedule without the need to manually check the status of each employee.
Technology Stack:
Make (Integromat)
REST API (JSON integration)
Google Sheets (Automation & Data management)
Result:
Complete Automation: The process of collecting and analyzing data now operates without human intervention.
Quality Control: Instant response to overdue reports has improved discipline on projects.
Time Savings: The management team has eliminated routine work, allowing them to refocus on analytics rather than data collection.
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56 USD Automated monitoring and instant notification system for m
Bot Development
The client needed to optimize the data collection process from questionnaires (Google Forms) and ensure instant delivery of structured reports to Telegram channels for two separate studios. The current process was chaotic and required manual verification of responses.
Solution:
Based on the Make (Integromat) platform, I developed an automated scenario:
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Integration: Automatic tracking of new responses in Google Forms for two different locations (studios).
Data processing: The scenario filters data, sorts selected survey items, and formats them into a structured list for easy reading.
Visualization in Telegram: Each completed questionnaire generates a clear, formatted message in the corresponding Telegram channel of the studio, allowing managers to respond instantly to feedback.
Result:
Complete elimination of manual processing of questionnaires.
Instant notification of managers and leadership.
Systematization of data, making it easier to analyze the studios' performance results.
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56 USD AI SEO Engine: Automated generation of HTML product descriptions for
AI & Machine Learning
Development of a high-performance system based on n8n for mass generation of SEO-optimized product descriptions in HTML format. The system automatically processes unstructured data (titles, characteristics, competitor texts) and transforms it into ready content for websites, using the DeepSeek and Gemini APIs.
Key advantages of implementation:
… 1. Batch Processing Workflow configured for stable processing of 100+ products in one run. The system automatically filters rows with the status NEW, allowing for the avoidance of duplication and efficient use of neural network API limits.
2. Multi-level generation logic (Main SEO Engine) Two parallel processing branches have been implemented:
Main SEO engine: Creation of a complete HTML description based on prepared prompts.
Name generator: A separate module for creating attractive titles (Name generation).
3. Full integration with Google Sheets The system operates as a "smart layer" for spreadsheets: it reads input data, performs intelligent processing, and writes the result back, automatically updating statuses (DONE / ERROR) and logging errors for reprocessing.
4. Flexibility and security (Production-Ready) The entire architecture is built without "hardcoding": prompts are loaded from a separate library, and access keys and confidential data are stored in environment variables. This allows for easy changes to the generation logic without interfering with the main code.
5. Intelligent error control In case of API failure or incorrect data, the system does not stop. It marks the problematic product with the status ERROR and records the reason for the error, allowing the manager to correct the data and restart processing only for the failed rows.
Conclusion: AI SEO Engine is a powerful tool for automating E-commerce. It replaces a team of copywriters, generating hundreds of product cards in minutes while adhering to all SEO and HTML formatting requirements.
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700 USD AI Calendar Orchestrator: Intelligent schedule management and
Bot Development
Development of an autonomous AI agent that transforms unstructured messages from Telegram into clear operations in Google Calendar. The system allows for managing work schedules, meetings, and tasks directly from the messenger, supporting complex editing logic and conflict checking.
Key benefits of implementation:
… 1. Intelligent Intent Recognition: The AI agent analyzes incoming messages from Telegram (text or voice) and automatically determines the necessary action: creating a new event, finding an available time slot, rescheduling a meeting, or deleting an outdated entry.
2. Multifunctional Calendar Manager (Full API Support): Unlike simple bots, this system has a complete set of tools for working with Google Calendar:
Create event with Attendees — automatic invitation of participants using their contacts.
Get/Update/Delete Events — full control over existing entries.
Contacts Search — integration with the contacts database for quick participant data retrieval.
3. Human-in-the-Loop: Control before publication: The system is implemented on the principle of security: after forming a request, the AI sends a draft event to the user in Telegram. Only after verification and pressing the "Approve" button does the agent perform the action in the calendar.
4. Working with complex models (GPT-4o & DeepSeek): Top language models are used to process requests, ensuring correct understanding of time zones, meeting durations, and conversation context.
5. Automatic conflict resolution: If another event is already scheduled for the chosen time, the agent will not just issue an error but will suggest alternative available slots to the manager based on current data from Google Calendar.
Conclusion: AI Calendar Orchestrator is a personal secretary that works 24/7. It eliminates the routine of manual data entry, reduces scheduling errors, and allows for managing all business meetings "on the go" through a convenient Telegram interface.
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557 USD AI Sales Copilot: Automation of personalized offers with many
Enterprise Resource Planning (ERP)
Development of an intelligent system for the sales department that prepares commercial proposals based on the analysis of previous projects of the company, but operates exclusively under the supervision of a manager. The main focus is the complete elimination of AI errors and "hallucinations" in communication with clients.
Key advantages of implementation:
… 1. Human-in-the-Loop Concept (Safety First) The system is designed so that AI does not have autonomous access to send emails. The prepared draft offer goes into a "waiting list" and remains there until a real manager checks it and changes the status to "Approved."
2. Intelligent Revision Agent (Revision Cycle) If the manager rejects the proposal and leaves a comment (for example, "too expensive" or "add a discount"), a specialized Revision Agent analyzes the edits, rewrites the text, and resubmits it for review. This allows achieving the perfect result without manual rewriting.
3. Historical Experience Analysis (Airtable Integration) The system is integrated with a database (Airtable), from which it pulls data on similar successful cases. This allows the AI to form proposals not "from scratch," but based on the real experience of the company and previous price offers.
4. Routine Automation without Quality Loss The manager spends only 30 seconds checking and pressing a button instead of 30 minutes compiling the document. The system independently classifies texts, selects the necessary models (GPT-4o / DeepSeek), and prepares the final letter.
Conclusion: AI Sales Copilot is the perfect solution for businesses where the cost of error is high. It combines the speed of artificial intelligence with the expertise of a live person, creating a reliable pipeline of personalized sales.
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600 USD Automated AI concierge: instant generation of tour packages and HT
Bot Development
Development of a full-cycle system for travel companies that automates the process of selecting complex tours. The AI independently searches for the best options for flights, hotels, and entertainment, forming a ready commercial proposal in just a few seconds.
Key advantages of implementation:
… 1. Parallel data processing (Multi-Stream Search) Thanks to n8n, the system simultaneously initiates searches in three directions: airline tickets, accommodation, and local events. This reduces the client's waiting time from 2 hours (manager's work) to 60 seconds.
2. Automatic generation of professional HTML offers The system aggregates the found data and automatically formats a stylish, responsive HTML letter. The client receives not just text in their email, but a full presentation of their vacation with photos, prices, and descriptions.
3. Use of AI for personalization The AI agent analyzes complex requests (for example: "I want something calm, but by the water, budget up to $2000") and selects only those options that 100% match the emotional and financial request of the client.
4. Integration with real data (Live API) The system operates through HTTP requests to search aggregators, ensuring the relevance of prices and availability at the moment of proposal formation.
Conclusion: This case demonstrates the possibility of scaling the travel business without increasing staff. One such assistant can handle hundreds of requests per day, providing instant responses to each client.
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1100 USD Multi-agent AI system for business process management via Telegram
AI & Machine Learning
Development of an intelligent management center based on n8n, which automates routine business tasks using a network of specialized AI agents. The system operates through a single interface in Telegram and is capable of independently determining which specialist to involve for executing a specific request.
Key advantages of implementation:
… 1. Intelligent routing (AI Orchestrator) The main AI agent analyzes each incoming message (text or voice) and instantly delegates it to the relevant sub-agent: Calendar, Email, Research, or Project Agent. This allows the system to work simultaneously with different types of tasks, ensuring high accuracy of execution.
2. Voice note processing (Speech-to-Action) Thanks to integration with OpenAI Whisper, the assistant not only transcribes voice but also extracts the essence from it. For example, dictating a task is automatically converted into a structured event in the calendar or a task in the CRM without any manual input.
3. Ecosystem of specialized agents Instead of a standard chatbot, the client gains access to a "digital staff":
Research Agent — conducts in-depth information searches on the web;
Email Agent — formulates and sends professional responses to partners;
Project Agent — monitors deadlines and project statuses.
4. Human-in-the-Loop: Full control The system is implemented based on the principle of secure assistance. Any critical action (send an email, change a meeting date) requires user confirmation. This guarantees complete control over AI actions and eliminates errors.
5. Scalability and efficiency The architecture based on n8n allows for easy addition of new agents or connection of additional APIs (Google Ads, CRM, ERP). This makes the system a universal tool that grows along with the business.
Conclusion: The multi-agent system is not just a bot, but a full-fledged digital office. It frees the owner or manager from routine tasks, providing instant responses to requests and perfect systematization in work.
Reviews and compliments on completed projects 11
14 March
70 USD
Improvement of the widget connecting AMO CRM with the invoicing service
Quality
Professionalism
Cost
Contactability
Deadlines
Everything quickly, qualitatively, excellent communication. Thank you very much.
Evgeniya Kristal
| Personal | Response review
12 March
215 USD
Operational chat analyzer API
Quality
Professionalism
Cost
Contactability
Deadlines
Excellent professional implementation of the project, taking into account the improvements. I recommend.
Stanisław Szumski
| Personal | Response review
2 March
81 USD
Control of photo reports API
Quality
Professionalism
Cost
Contactability
Deadlines
As always, the quality and speed of execution are top-notch.
Stanisław Szumski
| Personal | Response review
Quality
Professionalism
Cost
Contactability
Deadlines
Always in touch. Very high-quality work. I recommend for collaboration.
| Quality
Professionalism
Cost
Contactability
Deadlines
Promptly, clearly without unnecessary questions! I recommend for collaboration.
22 February
753 USD
Setting up the Digital ROP project
Quality
Professionalism
Cost
Contactability
Deadlines
Another complex project has been completed. We finished in half the time, with revisions and improvements. It is a pleasure to work with such a responsible and detail-oriented performer. This is not our first and will not be our last joint project!
Stanisław Szumski
| Personal | Response review
22 February
54 USD
Decomposition of the meeting - Digital ROP
Quality
Professionalism
Cost
Contactability
Deadlines
Very high level of professionalism, accuracy, and attention to detail.
Stanisław Szumski
| Personal | Response review
7 February
22 USD
Testing of the Telegram bot for data transmission (evaluation: 2–4 hours).
Quality
Professionalism
Cost
Contactability
Deadlines
The performer did an excellent job with the task. The bot was thoroughly tested, nuances were found and described that we ourselves might not have noticed. The work was done carefully and responsibly. I recommend for collaboration.
Andriy I
| Personal | Response review
28 January
56 USD
Automation of product description generation in n8n + deepseek / gemini
Quality
Professionalism
Cost
Contactability
Deadlines
Everything is fine, the performer is quick, sorry for the delay in acceptance.
20 January
323 USD
Setting up Voice AI (Make + Retell + Kommo)
Quality
Professionalism
Cost
Contactability
Deadlines
I can highly appreciate the involvement in the project. Quick and effective communication. I would also note the experience and knowledge on the issue, which helped to optimize and refine the initial project into a working case.
Stanisław Szumski
| Personal | Response review
18 January
16 USD
AI text translation
Quality
Professionalism
Cost
Contactability
Deadlines
Everything is great.
Vladislav did this task well.
I recommend the performer.
