Automated GL Coding for PR/PO Line Items
Assigns GL codes based on item-level data using Agentic AI, minimizing manual effort in procurement.
Key Features
Automatic GL code pre-filling
Automatically fills in the right GL codes based on the selected line items, saving time and reducing manual errors during PR creation.
Pre-trained on line items and codes
Trained on a wide range of line items and GL codes to suggest the most relevant codes for each purchase, ensuring accurate and context-aware recommendations.
Reduced Manual Efforts
Automatically assigns the right GL codes during PR creation, cutting down on manual steps and simplifying the process.
Seamless ERP integrations
Connects with ERP systems to apply the correct GL codes based on the organization's financial setup, keeping data aligned and accurate across platforms.
Override Capability for Flexibility
Allows users to adjust or replace suggested GL codes directly within the PR form, supporting custom allocations when needed.
Enhanced Accuracy and Compliance
Automatically fills GL codes to reduce manual errors and ensure expenses are recorded accurately and in line with financial guidelines.
KEY BENEFITS
Procurement Co-Pilot shrinks cycle times from request to purchase order, freeing teams from manual effort, delivering instant ERP-synced approvals, and giving finance teams real-time spend visibility for compliant, cost-effective purchasing.
80%
PO creation & dispatch time
Converts approved PR into PO automatically based on the company's templates. It can send POs automatically to vendors based on configurations.
5min
PR creation time
Co-pilot auto-fills most of the complex forms in ERPs and procurement systems by reducing the effort to 5 minutes
Auditability
Human Errors
Approvals
PO Closing & Other KPIs
Before and After Hyperbots PR/PO 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: GL Coding
How does the Co-Pilot perform GL coding automation?
The Co-Pilot analyzes each line item in the Purchase Requisition (PR) using its pre-trained AI platform. It automatically assigns the correct General Ledger (GL) codes by matching items with predefined rules and historical data, ensuring accurate expense allocation without manual effort.
Does the Co-Pilot learn from human manual selections?
Yes, the Co-Pilot continuously learns from user overrides. When users change recommended GL codes, the system updates its model to improve future accuracy, adapting to organizational preferences and accounting practices.
How much historical data is needed for effective GL coding automation?
The Co-Pilot requires a substantial amount of historical data, typically millions of annotated line items and GL codes. This extensive dataset allows the AI to recognize patterns and accurately assign codes across various procurement scenarios.
What are the benefits of automated GL coding with the Co-Pilot?
Automated GL coding reduces manual effort and minimizes errors in expense allocation. It ensures consistent and accurate GL code assignments, enhances compliance, speeds up PR creation, and allows procurement staff to focus on strategic tasks, boosting overall efficiency.
If a PR has multiple line items each with different expense accounts, how does the Co-Pilot handle it?
The Co-Pilot processes each line item individually, assigning the appropriate GL code based on its details and category. It ensures accurate allocation for each expense, even with multiple accounts, while allowing users to review and adjust codes as needed for precise management.
