Uladzislau Tropman's Work | ContraWork by Uladzislau Tropman
Uladzislau Tropman

Uladzislau Tropman

AI Automation & Low-Code Engineer | Python & JS

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Followed by GALLERY L and Hasan R

Mersin, Türkiye

WorkReviewsAbout

Mersin, Türkiye

Cover image for Overview Architected an end-to-end automated sales
Overview Architected an end-to-end automated sales funnel and content curation ecosystem powered by an AI Telegram bot. The pipeline manages user identification, mandatory subscription verification, automated lead magnet delivery, and 1-click omnichannel digest marketing. The Challenge Manual lead processing results in high lead leakage, lost contact details, and rapid user unsubscriptions right after receiving a free lead magnet. Marketing teams waste hours manually collecting content from scattered channels to design newsletters, without centralizing interaction logs. Tech Stack & Core Engineering • Lead Capture & Verification Layer: Deployed automated multi-step verification via Make (Integromat) checking channel subscription states and strictly forcing phone number capture before unlocking PDF access. • AI Digest Generation Core: Integrated Google Gemini AI to scrape raw channel posts, automatically parse relevance, filter out spam, and generate formatted HTML content summaries for marketing lists. • Moderation & Omnichannel Mailing: Programmed an interactive 1-click moderator interface inside Telegram allowing operators to approve or edit AI digests, instantly triggering a mass broadcast to the user database via Telegram and Gmail API. The Result • 100% phone number capture rate, securing total traffic retention into a centralized database. • Maximum reach with zero lead drop-offs by forcing high-intent channel subscriptions before file delivery. • Replaced 4 hours of daily manual copywriting with a 24/7 autonomous sales and auto-nurturing infrastructure.
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Cover image for Overview Engineered an autonomous FinTech pipeline
Overview Engineered an autonomous FinTech pipeline powered by an AI Telegram Bot to ingest, parse, and process raw Ziraat Bank statements (XLSX/PDF) into a consolidated Google Sheets accounting core. The system fully automates multi-currency asset tracking, expense classification, and dynamic moving exchange rate calculations. The Challenge Manual transfer of hundreds of banking transactions from spreadsheets causes critical accounting errors. Key operational hazards include miscalculated volume-weighted asset purchase prices, forgotten transaction fees, and broken formula dependencies across historical balance sheets. Tech Stack & Core Engineering • AI Analysis & Deduplication Layer: Integrated Google Gemini AI via Telegram API to instantly clean raw inputs, remove duplicate records, and interpret transaction intents for deposits, withdrawals, and split-commissions. • Scenario Routing Core: Configured multi-branch logic in Make (Integromat) to execute real-time accounting rules, automate 99/1 cash desk fee allocations, and trigger cross-currency conversions (TRY to USDT). • Apps Script Automation Engine: Programmed a high-performance Google Apps Script backend to handle 1-click ledger history recalculation, automated formula injection (D2 ranges), and real-time moving average tracking without breaking legacy financial data. The Result • 100% automated parsing of unstructured multi-bank statements with zero manual entry overhead. • Instant history recalculation loop enabling seamless, 1-click past transaction corrections. • 24/7 transparent balance sheet visibility and flawless data integrity across integrated asset registries.
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Cover image for Overview Engineered an intelligent, end-to-end sales
Overview Engineered an intelligent, end-to-end sales department automation pipeline powered by a custom Telegram bot. The system slashes post-call administrative routines by automatically generating personalized commercial proposals in PDF format, updating CRM pipelines, and notifying managers within 10 seconds of call completion. The Challenge Sales teams waste 7 to 10 minutes per client on manual CRM data entry, repetitive document template editing, and PDF conversions. This overhead limits managers to a maximum of 10 calls per hour while increasing human-factor errors and lead leakage. Tech Stack & Core Engineering • CRM Verification & Routing: Built advanced multi-branch conditional routing in Make (Integromat) to search for duplicate records by phone number or tax ID, dynamically updating existing cards or creating new ones with "Proposal Sent" status. • Document Generation Engine: Programmed automated data extraction that injects client variables directly into corporate letterheads, calculates custom pricing, and generates clean PDFs instantly. • Secure Infrastructure: Implemented fault-tolerant token authentication, secure SSL protocols, duplicate deal protection filters, and 24/7 logging via Google Sheets and Gmail SMTP. The Result • Boosted sales team performance from 10 to 25 calls per hour, achieving 2.5x operational growth. • Accelerated entire post-call lead processing and proposal delivery down to 10 seconds. • 100% elimination of manual data entry errors and duplicate deals within amoCRM.
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Cover image for Overview Architected a corporate-grade financial data
Overview Architected a corporate-grade financial data ingestion and auto-consolidation core for multi-entity holdings. The system processes raw multi-bank statements, eliminates internal group turnovers, and automatically populates a comprehensive 17-sheet management dashboard in 5 minutes with single-click execution. The Challenge Holding companies lose days of manual accounting labor when consolidating multi-entity records. Major pain points include double-counted internal loans, discrepancies across different bank formats, formula breakage, and a complete lack of granular ROI analytics per contract. Tech Stack & Core Engineering • Loading & Processing Layer: Programmed a highly optimized Google Apps Script backend engine containing over 1,540 lines of custom JavaScript code to handle auto-categorization via 100+ logical routing rules. • Automated Intercompany Settlements: Engineered custom two-way exclusion matrix filters using Python and Apps Script to isolate internal group transfers (Entity1 to Entity2), producing a clean net total with zero double-counting. • Analytical Layer: Designed a secure database core in Google Sheets running automated visualization via Google Charts to output granular contract breakdowns across 88 counterparties, plan-fact advance payment analysis, and automated balance sheets. The Result • Reduced multi-bank data consolidation time from 3 days to 5 minutes. • 100% mathematical precision with zero discrepancies or double-counted internal expenses. • Automated generation of 17 distinct management reports and deep ROI insights across 30 separate expense categories.
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