GL Coding
The Hyperbots PR/PO Co-Pilot streamlines the procurement process by automatically pre-filling GL codes based on line items using its pre-trained Agentic Al platform.
Key Features
Automatic GL code pre-filling
The co-pilot leverages the agentic AI platform to automatically pre-fill General Ledger (GL) codes based on the line items entered or selected by the requester, eliminating the need for manual entry.
Pre-trained on line items and codes
The system is pre-trained on extensive datasets of line items and corresponding GL codes, enabling accurate and reliable code recommendations tailored to specific procurement needs.
Reduced manual effort
By automating the GL code assignment, the co-pilot significantly reduces the effort required by individuals to manually search and enter appropriate codes, streamlining the PR creation process.
Seamless ERP integrations
The co-pilot integrates with ERP systems to ensure that the recommended GL codes are consistent with the organization's financial structure, enhancing data accuracy and consistency across platforms.
Override capability for flexibility
Users retain full control by having the ability to override the automatically recommended GL codes within the PR user interface, allowing for adjustments and custom allocations as needed.
Enhanced accuracy and compliance
Automated pre-filling minimizes human errors in GL code entry, ensuring that expenses are accurately allocated and compliant with financial policies and accounting standards.
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
VALUE PROPOSITION
Why Hyperbots Procurement
Co-Pilot?
Hyperbots PR/PO Co-pilot automates purchase requisition and order processes, including PR creation, approval workflows, and PO dispatch, ensuring efficiency, compliance, and seamless integration with ERP systems.
Before and After Hyperbots PR/PO Co-Pilot
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.
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.
Ready to take the next steps?
Book a demo with one of our Financial Technology Consultants to get started!