Accountant Bot: paper invoice parsing and intelligent data routing.
Replaced manual invoice logging with an intelligent AI pipeline. The manager simply drops a photo of a crumpled invoice in Telegram — Gemini parses the table data, normalizes measurement units (e.g., milliliters to liters), and automatically routes the records and scans into Google Drive and Google Sheets.
digitized automatically
spreadsheets
normalization
The headache of paper invoices
In Montenegro, less than 1% of vendors use electronic document exchanges (EDI). Nearly all stock delivery to restaurants and stores arrives with printed paper invoices.
To log a product delivery into the system, an accountant or manager must sit at a PC and copy-paste each item name, quantity, and price into endless Google Sheets. It is a grueling, repetitive chore that eats up hours and inevitably leads to typos, inventory mismatches, and discrepancies.
No Bot / With Accountant Bot
- Hours of manual data entry from physical invoices
- High human-error risk (price typos)
- Document photos lost in messy group chats
- Unit mismatches: vendor bills 750ml, but database requires liters
- Snap an invoice photo and drop it to a Telegram bot
- AI parses table text and returns a clean PDF draft for review
- Bot automatically converts 750ml to 0.75l for clean inventory metrics
- Archiving: scans upload straight to target Google Drive folders
Parsing, validation, and routing
We built a Serverless architecture powered by Supabase and Gemini Vision API. The entire document ingestion pipeline finishes in seconds and is guarded against LLM hallucinations with human-in-the-loop validation.
- Step 1: Parsing Vision API. The user snaps and sends an invoice photo to the bot. Gemini processes the image, reads the table structure, and extracts raw data.
- Step 2: Validation Review. The bot compiles the parsed rows into a clean PDF preview and sends it back to the user. The manager compares the PDF with the physical paper and taps "Confirm" if it matches.
- Step 3: Routing Google Drive. The bot automatically creates a dedicated archive folder on Google Drive and uploads both the original photo and the generated PDF.
- Step 4: Normalization Data Pipeline. The records are pushed into shared Google Sheets. Simultaneously, the bot normalizes metrics: if a vendor lists 750ml, the bot converts it to 0.75 liters so warehouse tracking balances correctly. Sheets are compiled in both Russian and Montenegrin.
We turned a crumpled piece of paper into a structured, normalized database record, saving the client dozens of hours of manual labor every month.