Configuring Accrual Policies with Agentic AI

Supports recurring expense accruals, GL coding, and automated processing through structured policy definitions.

 Configuring Accrual Policies with Agentic AI

Key Features

Configurable accrual policies

Configurable accrual policies

Enables flexible setup of accrual rules for cases like received goods or services that haven't been invoiced yet.

Recurring expense accruals

Recurring expense accruals

Automatically handles recurring expense accruals using set schedules and company policies.

Cut-off date accruals

Cut-off date accruals

Automatically creates accruals for invoices still pending at the cut-off date to support accurate financial reporting.

Manual accrual options

Manual accrual options

Gives accounting teams the flexibility to create accruals manually when needed.

Configurable accrual workflows

Configurable accrual workflows

Allows teams to customize approval and review steps in the accrual process to fit their specific requirements.

GL code management

GL code management

Manages company-specific accrual GL codes using either automated suggestions or custom configurations.

KEY BENEFITS

Accruals Co-Pilot automates detection, posting, and reversal, wiping out month-end busywork; machine learning sharpens forecasts and audit trails; policy-aware configuration snaps into any ERP—cutting errors, risk, and workload in one stroke.

80%

Accrual processing cost

Co-pilot reports all accrued expenses using AI eliminating the need for manual accruals completely

<5%

Variance in accured Vs actual costs

Co-pilot identifies all expenses comprehensively for all type of scenarios through data using AI.

Human Errors

Accrual reversal

Month end closing pressure

Auditability

Accruals before and after

Hyperbots Accruals Co-Pilot

Why Hyperbots Agentic AI Platform?

Why choose hyperbots agentic AI: finance-first, accurate, adaptable AI

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.

Designed by CFOs for CFOs

We worked with several CFOs to solve the right problems.

Hear what they have to say!

Designed by CFOs for CFOs

We worked with several CFOs to solve the right problems.

Hear what they have to say!

Ready to take the next steps?

Book a demo with one of our Financial Technology Consultants to get started!