Automating Accrual Reversals for Month-End Close
Allows flexible reversal of accrued expenses at the start of the month or during invoice processing, to support accurate and timely accrual automation.
Key Features
Beginning of Next Month Reversals
Reverses accrued expenses at the start of the next month to align with monthly accounting practices.
Real-time reversals
Automatically reverses accruals as soon as the related invoice is processed, keeping expense records up to date.
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 ERPโcutting 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
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.

Abbott

AbbVie

Amazon

Apple

Arrow Electronics

AT&T

AutoNation

Bank of America

Berkshire Hathaway (GEICO)

CBRE

Cigna Group

Cisco Systems

Citigroup

Costco

Dell Technologies

Dollar Tree

Duke Energy

Eli Lilly

ExxonMobil

FedEx

Goldman Sachs

Honeywell

HP / Hewlett Packard Enterprise

IBM

Jewel-Osco (Albertsons)

JLL

Johnson & Johnson

Liberty Mutual

Lowe's

Marathon Petroleum

Marriott International

Mastercard

McKesson

Medline

MetLife

PepsiCo

Pfizer

Phillips 66

Progressive

Southwest Airlines

Starbucks

Stryker

The Home Depot

Travelers

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Valero Energy

Walmart

Warner Bros. Discovery

3M

Allstate

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Best Buy

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Chevron

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Cummins

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General Dynamics IT

Google (Alphabet)

Humana

International Paper

JPMorgan Chase

Kraft Heinz

Kroger

Marsh McLennan

McDonald's

Merck & Co.

Microsoft

Mondelez

Nationwide

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Southern Company

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Thermo Fisher Scientific

Uber

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UnitedHealth Group (incl. Optum)

UPS

US Foods

Verizon

Waste Management

Wells Fargo