Finance Teams: Reconcile Data Faster and Forecast Smarter

aidnn helps finance teams turn messy GL data, billing exports, and operational signals into verified analysis in minutes, not weeks.

Finance AI three-way reconciliation demo showing Isotopes AI | aidnn comparing business plan, general ledger actuals, and purchase order commitments to identify budget variance.

Three-way Reconciliation Between BP, GL and PO

Run three-way reconciliation between business plan in Anaplan, general ledger in SAP FI and
purchase orders in SAP MM.

How It Works

What Finance Teams Use aidnn For

From the monthly close to board prep, aidnn handles your most complex, data-rich workflows without a data engineering team.

Accrual Risk Analysis

Run period close quality and accrual risk management analysis.

Opex Projection by Profit Center

Analyze operating expenses, forecast financial performance, and reconcile profit center data with AI insights.

Cashflow Forecast and Burn-down Analysis

Build a cash flow forecast and open-commitment burn-down for Meridian Holdings.

The Problem

Finance Data Lives Everywhere

aidnn is built to verify every number

From GL exports across NetSuite, Sage Intacct, and Oracle to billing data in Stripe, Salesforce, and a long tail of spreadsheets, your numbers live in systems that don't reconcile, which makes verifying answers nearly impossible for most LLMs.

  • ERPs, billing, and CRM systems don't connect, forcing analysts to spend 60-70% of their time on data prep.

  • Joining data across NetSuite, Salesforce, Stripe, and HRIS takes weeks every quarter.

  • Analytics are slow, error-prone, and sensitive financial data can't leave your environment.

NeoCortex connecting and reconciling datasets to prepare verified, AI-ready data for analytics.

The Intelligence Layer Behind Better Financial Decisions

Verify Consistent Financial Analysis with aidnn

95%

Time saved on flux analysis (week → hours)

40%

Reduction in accrued liability review workload

5X

Faster on multi-source, multi-step workflows

0

Data engineers needed to get answers


From Messy Data to Clear Decisions

aidnn deploys a team of specialized agents, not a single model, built to handle the complexity of multi-source finance data with full transparency at every step.

Frequently Asked Questions

What does aidnn do for finance teams?

aidnn is an AI agent that turns messy GL data, billing exports, and operational signals into verified financial analysis in minutes. It cleans and reconciles data across systems that don't agree, runs the analysis, and independently verifies every step before a number reaches you. Finance teams use it for month-end close, flux analysis, reconciliation, forecasting, and board prep.

Which finance systems does aidnn connect to?

aidnn connects to ERP, billing, and CRM systems including NetSuite, SAP, Sage Intacct, Oracle, Stripe, Salesforce, and QuickBooks, plus Snowflake, BigQuery, Postgres, and Excel and CSV files. It works with data as it exists today, so you don't need to clean or model it first.

How does aidnn verify financial numbers?

A separate critic agent reviews every plan, query, and result before it reaches you, and it holds veto authority over logic, math, and code. Verification runs inline as the analysis executes and again more deeply afterward. Every step is logged, so you can reproduce any decision and defend any number.

Can aidnn handle data that doesn't reconcile across systems?

Yes. That's the primary use case. aidnn is built for data that is structurally fragmented rather than simply dirty, where the same entity is defined differently in each system. It reconciles those definitions as part of the analysis rather than requiring a data engineering project first.

How much does aidnn cost?

Pricing is custom. aidnn is sold as an enterprise product through our sales team, and there is no public price list or self-serve tier. Contact sales for pricing.

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Ready to put aidnn to work?

We run free, structured POCs. Bring your messiest GL or close dataset. We'll show you what's possible.

Financial data reconciliation dashboard interface showing file upload section with multiple PDF files listed and a note explaining reconciliation instructions for Q1 2025 vendor invoices and expense reports.