BILL Spend & Expense (formerly Divvy)
Total visibility and control over business spend with automated expense management and smart corporate cards.
Docyt is a leading-edge AI-driven accounting automation platform designed to transform the back office from a reactive cost center into a real-time strategic asset. Architecturally, Docyt functions as a sophisticated data orchestration layer that sits atop traditional General Ledgers (GL) like QuickBooks Online and Sage Intacct. By leveraging proprietary Machine Learning models and Large Language Models (LLMs) for document classification and data extraction, it eliminates manual data entry and provides continuous reconciliation. By 2026, its market position is defined by its 'Sub-ledger' technology, which allows businesses to track granular financial data at the department or location level without cluttering the primary GL. The system employs a multi-tenant architecture optimized for franchises and multi-entity enterprises, offering automated vendor bill pay, employee expense management, and revenue reconciliation. Its technical differentiation lies in its 'Autonomous Bookkeeping' engine, which uses semantic mapping to categorize transactions based on historical patterns and industry-specific logic, effectively reducing the monthly close cycle from weeks to hours while maintaining a SOC2-compliant data integrity environment.
Maintains a granular secondary ledger for departmental tracking that syncs summary data to the primary ERP, preventing GL bloat.
Total visibility and control over business spend with automated expense management and smart corporate cards.
AI-First Intelligent Document Processing for the Autonomous Enterprise
Autonomous purchase invoice processing and financial intelligence layer for modern ERPs.
Automate financial document collection and data entry for seamless accounting reconciliation.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Proprietary algorithms that match bank statements, merchant processing reports, and internal invoices with 99.2% precision.
Conditional logic engine that routes bills and expenses based on dollar amount, GL code, or department head.
Automated cross-referencing of POS data (Toast, Square, Clover) against bank deposits to identify leakage.
Transformer-based OCR that extracts line-item data from complex utility bills and vendor invoices.
Automated screening of vendor tax IDs and bank details to prevent fraudulent payments.
Predictive analytics based on historical burn rates and scheduled accounts payable.
Consolidating 50 different P&L statements took 20 days every month.
Registry Updated:2/7/2026
Discrepancies between Shopify sales, Stripe payouts, and bank deposits.
Difficulties tracking expenses against specific job codes in real-time.