Build an Automatic AI Accountant With Muse, Unsiloed, and Jev

Описание и применение

Автоматизированный бухгалтер, работающий в Muse, использует Unsiloed для чтения документов и Jev для принятия решений о классификации записей, позволяя малому бизнесу вести бухгалтерию без человека.

Задача

Small businesses need a way to reconcile receipts, bills, payouts, and bank statements into a ledger without a human accountant.

Результат

The system processed eight documents for a glassblowing studio, produced a reconciled ledger, and delivered a month‑end pack with a profit of $2,194.47, correctly categorizing a $6,670 oven as equipment and splitting a payout into gross income and platform fee.

Рабочий процесс

• Owner attaches month’s documents to Muse
• Muse calls Unsiloed /v2/extract for each document type
• Unsiloed returns fields with confidence scores and citations
• Python code validates totals, bank balances, asset thresholds, duplicates, and bank matches
• Jev model answers narrow yes/no or choice questions about account classification, personal vs business, asset status, duplicates, and payments
• Muse aggregates results, books entries, and saves owner responses as rules for future months
• Muse generates month‑end pack (profit & loss, assets, liabilities, bank reconciliation) and sends to owner

Доказательства

In the age of AI, a small business shouldn't need an accountant to keep its books.

Источник

It asks the owner only about the items it can't settle, in plain English.

Источник

Unsiloed’s /v2/extract endpoint takes a JSON schema for each document type and returns every field with a confidence score and, with enable_citations on, a bounding box on the page.

Источник

Jev judges only what's left. Code decides that the annealing oven costs more than $2,500, and Jev decides whether it's durable equipment.

Источник