Tax Preparation

Tax preparation automation collects primary documents from various sources, extracts their details and amounts, checks consistency with the accounting system, and prepares a summary that the accountant starts with. The goal is to eliminate manual data transfer from PDFs, scans, and emails into accounting records, so the team spends time on review and decision-making rather than retyping.

What automation does, step by step

1. Collects documents from connected sources: corporate email, folders in cloud storage (Google Drive, Dropbox, OneDrive, S3), shared chats with suppliers, inbound from EDI.
2. Recognizes content: applies OCR to scans and photos, parses PDFs and Excel files, extracts text from emails and attachments.
3. Extracts details: counterparty, TIN/EDRPOU, document number and date, amounts (total, excluding VAT, VAT), currency, expense or income category.
4. Classifies documents by type (invoice, completion certificate, waybill, bank statement, cash receipt, contract) and by accounting category based on company rules and history.
5. Reconciles with the accounting system: checks whether the document exists in accounting records, whether amounts match, and whether the entry is duplicated.
6. Flags discrepancies and gaps: documents with no matching entry in accounting, incomplete details, counterparties without a TIN, suspicious duplicates.
7. Generates a summary for the accountant: list of documents for the period, statuses (ready / requires clarification / error), aggregates by category and counterparty, export to Excel or direct upload to the accounting system.

What automation does NOT do

• Does not submit reports to the tax authority or sign declarations with an electronic signature — that is the accountant's responsibility.
• Does not interpret complex tax situations: disputed expenses, asset reclassification, and non-standard transactions go to manual review.
• Does not replace the accountant: the final review of the summary, tax calculation, and decision-making on ambiguous documents are performed by a person with relevant expertise.

The automation works as a pipeline of sequential stages: a trigger on a new document, recognition, extraction, validation, classification, reconciliation, and export. Each stage is responsible for its own task and logs the result, so that when an error occurs it is possible to identify where it broke.

Technical flow

The sources are corporate email, folders in file storage, and the accounting system API. The AI agent polls them on a schedule or subscribes to webhooks, places new documents into the processing queue, and proceeds through the stages:

1. Pre-processing: unpacking archives, extracting attachments from emails, normalizing formats (PDF → text, scan → OCR text).
2. Extraction: an LLM with a defined JSON schema extracts document fields. For standard forms it works faster (regex + rules); for non-standard ones — fallback to LLM.
3. Validation: checking required fields (counterparty, amount, date), formal validation of ИНН/EDRPOU, arithmetic check (amount = base + VAT).
4. Classification: the model assigns the document to a type and accounting category. It uses the company's history — trained on already-posted documents from previous periods.
5. Reconciliation: a request to the accounting system via API or CSV export-import; matching by number, date, counterparty, and amount.
6. Output: a summary in Excel/Google Sheets format, export to accounting, notification in Slack or email to the accountant with a list of documents requiring attention.

Implementation steps

1. Document flow audit: what types of documents flow through the company, in what formats, how many per month, where they are stored.
2. Description of classification rules: a list of expense/revenue categories, typical counterparties, specifics of the accounting policy.
3. Connecting sources: configuring access to email (IMAP or OAuth), cloud folders, and the accounting system API.
4. Configuring the extraction pipeline: selecting models and rules for the specific document formats used by the company.
5. Calibration on historical data: running on documents from the previous quarter, comparing the result with what was posted by the accountant, correcting classification errors.
6. Pilot on a single stream: 2-3 weeks of operation only on bank statements or only on supplier invoices.
7. Gradual rollout: connecting the remaining document types and expanding the list of sources.
8. Handover to operations: a dashboard with metrics (% of automated processing, average time from receipt to summary, share of documents requiring manual correction), and a procedure for accountant actions when alerts trigger.

Solution components

The stage of calibration on historical data delivers the main accuracy gain: the more past documents with accountant markup the classifier sees, the fewer manual corrections in operation.

Three readiness blocks are required before launch: data, access, and team.

Data and systems

• Accounting system with API or CSV/Excel import capability: 1С, BAS, MeDoc, Xero, QuickBooks, or a niche accounting SaaS.
• Cloud storage for incoming documents: Google Drive, Dropbox, OneDrive, S3, or equivalent. Folder structure is not required but recommended.
• Corporate email access, which receives invoices and acts from suppliers: an IMAP account or OAuth integration.
• Historical documents for 3-6 months with completed labeling in the accounting system — needed for classifier calibration.
• Chart of accounts and list of line items of expenses/income in a format readable by the system.

Team and roles

• Chief accountant or CFO — process owner, validates classification rules and the summary format.
• IT administrator or contractor — configures access to email, cloud storage, and the accounting system.
• Document flow manager — monitors source completeness, reviews alerts in the first weeks after launch.

Implementation timeline

A realistic range — 6-10 weeks for average document flow complexity:

1. Document flow audit and rules definition — 1-2 weeks.
2. Connecting sources and configuring the extraction pipeline — 2-3 weeks.
3. Classifier calibration and pilot on one direction — 2-3 weeks.
4. Full rollout and handover to operations — 1-2 weeks.

If the company has multiple legal entities, different accounting systems, or a complex document structure, the timeline is closer to the upper boundary.