Structured Line Item Extraction for Sales Tax
Uses multi-model intelligence to extract line items, match invoices, and support tax accuracy in journal entries.
Key Features
Multi-model field extraction
Uses a mix of AI models to understand both structured and unstructured data, like fields, free-text, and table layouts, ensuring line items are read and validated accurately.
Pre-training on 35 million invoice fields
Trained on millions of real-world invoices, the system reliably handles a wide range of formats, vendors, and industry-specific layouts.
Field-specific model optimization
Different types of fields, like numbers, dates, or line items, are processed using models designed for each, helping improve accuracy and reliability across the board.
Chain-of-thought reasoning
Applies step-by-step reasoning to understand how related fields connect, helping ensure consistent and accurate data interpretation.
Line-item parsing with spatial intelligence
Uses layout awareness to read and organize line items from tables, even when they span multiple rows or columns on the invoice.
Intelligent line-item validation
Checks that quantities, prices, totals, and taxes all add up correctly, helping catch errors and ensure accurate line-item entries.
KEY BENEFITS
Hyperbots Sales Tax Verification Co-Pilot locks in sales-tax compliance on every invoice, shutting down tax underpayment penalties before they start. A built-in, time-stamped trail delivers effortless auditability, while near-zero human errors protect margins and, ultimately, your company’s reputation for accuracy and integrity.
Sales tax compliance
Co-pilot verifies applicable sales tax for every invoice and line item automatically
Tax underpayment
Co-pilot acts as a preventive method against over or under-charged sales tax by vendors
Auditability
Human errors
Reputation
Before and After Hyperbots Sales Tax Verification Co-Pilot
Why Hyperbots Agentic AI Platform?
Finance specific
Hyperbots Agentic AI platform specializes exclusively in finance and accounting intelligence, leveraging millions of data points from invoices, statements, contracts, and other financial documents. No other platform has such large pretrained models on F&A data.
Best-in-class accuracy
Hyperbots achieves 99.8% accuracy in converting unstructured data to structured fields through a multimodal MOE model integrating LLMs, VLMs, and layout models. With contextual validation and augmentations, the platform ensures 100% accuracy for deployed agents.
Synthesis of unstructured and strutured finance data
Hyperbots agents emulate finance professionals to autonomously perform F&A tasks by reading and writing data like COA, expenses, and vendor masters from core accounting systems and integrating it with unstructured data from financial documents such as invoices, POs, and contracts.
Pre-trained agents with state of the art models
Hyperbots' Agentic platform, pre-trained on millions of financial documents like invoices, bills, statements, and contracts, ensures seamless integration, high accuracy, and adaptability to any accounting content, form, layout, or size from day one.
Company specific inference time learning
Hyperbots' Agentic platform employs state-of-the-art Auto ML pipelines with techniques like reinforcement learning to enable inference-time learning for tasks such as GL recommendation and cash outflow forecasting, ensuring continuous improvement and adaptability.
FAQs: Extraction and Validation of Line Item Details
How does the Hyperbots Co-pilot extract and validate line items?
Hyperbots leverages multi-model AI—combining vision-language models to detect structured elements (like tables and columns) and large language models (LLMs) to interpret unstructured text. It extracts each line item’s details (e.g., description, quantity, unit price) and validates them by cross-referencing fields such as net amount, tax amount, and other invoice data.
Can Hyperbots identify line items if there are hundreds spread across multiple tables in complex invoices?
Yes. Hyperbots’ advanced table-parsing algorithms and spatial intelligence enable it to handle multiple tables, nested formats, and high-volume line items. It accurately segments invoice sections and reliably captures each individual entry, regardless of complexity or length.
Does the Hyperbots Co-pilot convert line item information into structured fields?
Absolutely. Once the system has extracted line item details, it organizes them into structured data fields (e.g., item code, quantity, unit price, total) for easy downstream processing, integration with accounting systems, and accurate tax computation.
What validations does it perform?
The Co-pilot checks for consistency between related fields (e.g., quantity × unit price = extended amount, correct tax rates applied, net amount plus tax = gross amount). It flags discrepancies, suggests corrections, and ensures compliance with applicable tax regulations or contract terms.
Why is extraction and validation of line items important for sales tax verification?
Accurate sales tax calculation relies on a precise breakdown of each line item’s taxable status and amount. Validating line items reduces errors in tax reporting, minimizes compliance risks, and helps organizations avoid over- or under-payment of taxes.
