Straight Through Processing in Finance & Accounting
Experience real straight-through processing with Agentic AI fully automating invoice intake, matching, approvals, and posting in one seamless workflow.
Key Features
Email Parsing and Invoice Discovery
Invoices are automatically picked from emails, portals, and drives. The Co-pilot uses AI-based filtering to eliminate anything that’s not an invoice.
Intelligent Invoice Field Extraction
Key invoice fields like vendor info, amounts, and tax details are auto-extracted using pre-trained AI models.
Dynamic GL Coding
The Co-Pilot auto-assigns GL codes using item details, vendor info, and past company data, no manual coding needed.
2-Way and 3-Way Matching
The Co-Pilot checks invoices against POs and delivery notes to make sure everything matches, right down to the line items. Example: A PO lists 100 units of a product at $50/unit. The Co-pilot verifies the invoice matches the PO, and the GRN confirms delivery.
Line Item-Level Validation
Agentic platform validates the fields of invoice with agentic reasoning for field co-relationships, contextual correctness or appropruatenes against the ground truth
Tax and Payment Term Validation
The Co-pilot verifies tax calculations and payment terms on invoices, ensuring they align with company policies and legal requirements. Example: Validating a “Net 30” payment term and ensuring tax rates comply with jurisdictional standards.
Exception Handling with Human-in-the-Loop
For 20% of invoices with business exceptions, the Co-pilot flags issues for human intervention. Example: An invoice with mismatched line items or missing PO reference is routed to the accounts payable team for review.
Real-Time Integration with ERPs
The Co-pilot integrates with ERPs like SAP, NetSuite, and QuickBooks for seamless invoice posting and reconciliation. Example: Posting an invoice directly to NetSuite after validation.
Error Correction and Feedback Loop
The system incorporates a feedback loop to verify each transaction. If a write operation to the ERP fails, the Co-pilot retries and reports unresolved errors for corrective action. Example: If an invoice fails to post to the ERP due to a missing GL code, the issue is flagged for resolution.
Scalable and Adaptive Agentic AI
The Co-pilot adapts to diverse invoice formats and workflows across industries, using pre-trained fine-tuned AI models for specific use cases. Example: Handling retail invoices with discount details or construction invoices with project-specific fields.
High Accuracy with Pre-Trained Models
Achieving 99.8% field extraction accuracy, the Co-pilot ensures reliable invoice processing with minimal errors. These Hyperbots Agentic AI capabilties are deeplay nuanced and patent pending. Co-pilots leverage all of these to achieve STP.
KEY BENEFITS
Achieve 80 % straight-through invoice processing as AI discovers, extracts, validates, matches, GL-codes, and posts to your ERP—shrinking manual effort, accelerating approvals, and boosting accuracy, compliance, and cost efficiency.
80%
Invoice processing cost
AI achieves up to 80% straight-through processing of invoices, freeing up staff bandwidth by 80%. Retained staff is empowered by Co-pilot with pin-pointed reasons to take quick decisions on business exceptions reported.
<1 min
Invoice processing time
Co-pilot reduces invoice processing time from an industry average of 11 days to less than one minute due to STP achieved through AI.
Human errors
Vendor satisfaction
Duplication & frauds
Auditability
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: Straight through processing
What can be the audit method for STP transactions?
STP transactions can be audited using Hyperbots’ detailed audit trails, which log every action taken by the Co-pilot, including data extraction, validations, matching results, and posting details. Spot audits or full audits can be conducted as needed.
What is the role of humans when invoices go from source to GL without human touch?
Humans are involved in overseeing exceptions flagged by the Co-pilot, reviewing audit trails, and periodically evaluating AI performance to ensure compliance and accuracy.
What can be done for non-PO invoices to bring them into the STP paradigm?
Non-PO invoices can be incorporated into STP by leveraging Hyperbots’ GL recommendation engine, which learns from historical postings and applies contextual validation to ensure accurate processing.
Do we execute STP from day one, or is there a phased approach to reach the STP goal?
Hyperbots recommends a phased approach, starting with partial automation to validate AI accuracy and gradually expanding to full STP as confidence and alignment with business rules are achieved.
How can users trust Hyperbots' STP output?
The Co-pilot provides detailed audit trails for every STP transaction, including timestamps, validation steps, and AI actions. Additionally, Hyperbots allows users to review initial outputs during a phased STP implementation to build confidence.
How has Hyperbots solved these two challenges?
Hyperbots uses multimodal MOE (Mixture of Experts) models trained on millions of invoices to achieve near-perfect accuracy in data extraction and validation. Its advanced contextual validation and augmentation algorithms handle exceptions automatically, enabling seamless STP.
What are the top two challenges that no one has solved to achieve STP?
Accurately understanding unstructured invoice data in various formats, layouts, and languages without human touch automated GL coding for each line item.