I turn raw, messy business data into a reporting layer a decision-maker actually reads: a one-glance dashboard (spend by month/category, price movements), breakdowns by supplier and category, price-trend tracking, and a ledger where every figure reconciles (net + VAT = gross, totals tie back). Rebuilds into a multi-sheet Excel workbook. Works from any CSV, spreadsheet or accounting export.
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A Telegram bot that turns any invoice or receipt photo into a verified Excel record: OCR extracts supplier, tax ID, dates, net/VAT/gross and line items; every document is arithmetic-checked (net + VAT = gross) and duplicates are caught. One command exports a multi-sheet workbook. Live 6 months: 484 documents, 135 suppliers, 75 mismatches auto-caught, zero manual entry.
Market research brief — one page first, a source for every number. Sample layout with illustrative figures: importers of engineered wood in the Gulf, market size by country, who buys, who sells to them now, where to start.
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Verified B2B lead list — sample delivery. Every row: company from an official registry, decision-maker with role, email checked on the mail server, source link. Names blurred for client confidentiality.
Analyzed revenue lifecycle using cohort tables and MMR tracking. Visualized user payment behavior, retention shifts, and total revenue dynamics for data-driven growth.
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Comprehensive financial analysis across USA, EMEA, and APAC. Tracks ARPPU, Paid User dynamics, and revenue by software category to drive global growth strategy.