Accelerate your month-end close

AI Financial Reconciliation Agent

Reconcile accounts in minutes, not days

Delegate your most tedious financial task to a specialized AI agent. It automatically compares transactions between any two sources—bank statements, invoices, GL reports—and instantly highlights the exceptions that require your attention.

Ideal for

Accounting

Audit & Assurance

Financial Operations

  • Mercedes-Benz logo
    SMC  logo
    Philips logo
    Bayer Logo
    Mars Logo
    Roche logo
    Sony logo
    Alaris logo

See AI Financial Reconciliation Agent in action

Play video

  • Mercedes-Benz logo
    SMC  logo
    Philips logo
    Bayer Logo
    Mars Logo
    Roche logo
    Sony logo
    Alaris logo

See AI Financial Reconciliation Agent in action

Play video

  • Mercedes-Benz logo
    SMC  logo
    Philips logo
    Bayer Logo
    Mars Logo
    Roche logo
    Sony logo
    Alaris logo

See AI Financial Reconciliation Agent in action

Play video

Bank Reconciliation

  • Mercedes-Benz logo
    SMC  logo
    Philips logo
    Bayer Logo
    Mars Logo
    Roche logo
    Sony logo
    Alaris logo

See AI Financial Reconciliation Agent in action

Play video

Time comparison

Time comparison

Traditional way

2-3 days per month

2-3 days per month

With V7 Go agents

30 minutes

30 minutes

Average time saved

95%

95%

Why V7 Go

Why V7 Go

Multi-Source Reconciliation

Compares any two data sources, including bank statements vs. general ledger, credit card statements vs. expense reports, or accounts receivable sub-ledgers vs. cash receipts.

Multi-Source Reconciliation

Compares any two data sources, including bank statements vs. general ledger, credit card statements vs. expense reports, or accounts receivable sub-ledgers vs. cash receipts.

Multi-Source Reconciliation

Compares any two data sources, including bank statements vs. general ledger, credit card statements vs. expense reports, or accounts receivable sub-ledgers vs. cash receipts.

Multi-Source Reconciliation

Compares any two data sources, including bank statements vs. general ledger, credit card statements vs. expense reports, or accounts receivable sub-ledgers vs. cash receipts.

Intelligent Transaction Matching

Goes beyond exact matches by using AI to identify likely pairs based on amount, date proximity, and description details, dramatically increasing the automated match rate.

Intelligent Transaction Matching

Goes beyond exact matches by using AI to identify likely pairs based on amount, date proximity, and description details, dramatically increasing the automated match rate.

Intelligent Transaction Matching

Goes beyond exact matches by using AI to identify likely pairs based on amount, date proximity, and description details, dramatically increasing the automated match rate.

Intelligent Transaction Matching

Goes beyond exact matches by using AI to identify likely pairs based on amount, date proximity, and description details, dramatically increasing the automated match rate.

Automated Exception Identification

Automatically generates a clean report of only the items that need human attention, such as unmatched transactions, timing differences, or coding errors.

Automated Exception Identification

Automatically generates a clean report of only the items that need human attention, such as unmatched transactions, timing differences, or coding errors.

Automated Exception Identification

Automatically generates a clean report of only the items that need human attention, such as unmatched transactions, timing differences, or coding errors.

Automated Exception Identification

Automatically generates a clean report of only the items that need human attention, such as unmatched transactions, timing differences, or coding errors.

Complex Statement Parsing

Reads and extracts data from unstructured PDF bank and credit card statements, turning them into a structured format ready for comparison against your internal records.

Complex Statement Parsing

Reads and extracts data from unstructured PDF bank and credit card statements, turning them into a structured format ready for comparison against your internal records.

Complex Statement Parsing

Reads and extracts data from unstructured PDF bank and credit card statements, turning them into a structured format ready for comparison against your internal records.

Complex Statement Parsing

Reads and extracts data from unstructured PDF bank and credit card statements, turning them into a structured format ready for comparison against your internal records.

Custom Matching Rule Configuration

Define your own specific reconciliation rules, such as a tolerance threshold for small discrepancies or a rule for handling specific transaction types, to tailor the automation to your business.

Custom Matching Rule Configuration

Define your own specific reconciliation rules, such as a tolerance threshold for small discrepancies or a rule for handling specific transaction types, to tailor the automation to your business.

Custom Matching Rule Configuration

Define your own specific reconciliation rules, such as a tolerance threshold for small discrepancies or a rule for handling specific transaction types, to tailor the automation to your business.

Custom Matching Rule Configuration

Define your own specific reconciliation rules, such as a tolerance threshold for small discrepancies or a rule for handling specific transaction types, to tailor the automation to your business.

Audit-Ready Workpapers

Generates a clear, auditable reconciliation report that shows the full population of transactions, the items that matched, and the exceptions that were investigated, supporting a clean audit.

Audit-Ready Workpapers

Generates a clear, auditable reconciliation report that shows the full population of transactions, the items that matched, and the exceptions that were investigated, supporting a clean audit.

Audit-Ready Workpapers

Generates a clear, auditable reconciliation report that shows the full population of transactions, the items that matched, and the exceptions that were investigated, supporting a clean audit.

Audit-Ready Workpapers

Generates a clear, auditable reconciliation report that shows the full population of transactions, the items that matched, and the exceptions that were investigated, supporting a clean audit.

Customer voices

Customer voices

Connect AI to your financial systems.

Connect AI to your financial systems.

Turn your manual month-end close into a fast, automated workflow.

Turn your manual month-end close into a fast, automated workflow.

Finance

Legal

Insurance

Tax

Real Estate

Finance

Legal

Insurance

Tax

Real Estate

Finance

Legal

Insurance

Tax

Real Estate

Customer Voices

Features

Features

Results you can actually trust.
Reliable AI document processing toolkit.

Results you can trust.
Trustworthy AI document processing toolkit.

Supporting complex documents.

Up to 200 pages.

Financial data lives in many formats. This agent ingests transaction data from any source, including multi-page PDF bank statements, CSV exports from your ERP, and scanned credit card receipts, to create a unified view.

Input types

50+ languages

Data Feeds

200 pages

Multi-modal

Document types

PDFs

CSV Files

Complex Tables

Low-Quality Scans

Spreadsheets

Vendor_US.xlsx

3

Supply_2023.pptx

Review_Legal.pdf

Supporting complex documents.

Up to 200 pages.

Financial data lives in many formats. This agent ingests transaction data from any source, including multi-page PDF bank statements, CSV exports from your ERP, and scanned credit card receipts, to create a unified view.

Input types

50+ languages

Data Feeds

200 pages

Multi-modal

Document types

PDFs

CSV Files

Complex Tables

Low-Quality Scans

Spreadsheets

Vendor_US.xlsx

3

Supply_2023.pptx

Review_Legal.pdf

Supporting complex documents.

Up to 200 pages.

Financial data lives in many formats. This agent ingests transaction data from any source, including multi-page PDF bank statements, CSV exports from your ERP, and scanned credit card receipts, to create a unified view.

Input types

50+ languages

Data Feeds

200 pages

Multi-modal

Document types

PDFs

CSV Files

Complex Tables

Low-Quality Scans

Spreadsheets

Vendor_US.xlsx

3

Supply_2023.pptx

Review_Legal.pdf

Reach 99% accuracy rate

through GenAI reasoning.

A clean financial close depends on precise matching. The agent uses AI reasoning to intelligently identify likely matches based on amounts and dates, and is configured to handle complex scenarios like one-to-many transactions.

Model providers

Security note

V7 never trains models on your private data. We keep your data encrypted and allow you to deploy your own models.

Answer

Type

Text

Tool

o4 Mini

Reasoning effort

Off

Low

Mid

High

AI Citations

Inputs

Set a prompt (Press @ to mention an input)

Reach 99% accuracy rate

through GenAI reasoning.

A clean financial close depends on precise matching. The agent uses AI reasoning to intelligently identify likely matches based on amounts and dates, and is configured to handle complex scenarios like one-to-many transactions.

Model providers

Security note

V7 never trains models on your private data. We keep your data encrypted and allow you to deploy your own models.

Answer

Type

Text

Tool

o4 Mini

Reasoning effort

Off

Low

Mid

High

AI Citations

Inputs

Set a prompt (Press @ to mention an input)

Reach 99% accuracy rate

through GenAI reasoning.

A clean financial close depends on precise matching. The agent uses AI reasoning to intelligently identify likely matches based on amounts and dates, and is configured to handle complex scenarios like one-to-many transactions.

Model providers

Security note

V7 never trains models on your private data. We keep your data encrypted and allow you to deploy your own models.

Answer

Type

Text

Tool

o4 Mini

Reasoning effort

Off

Low

Mid

High

AI Citations

Inputs

Set a prompt (Press @ to mention an input)

Trustworthy results,

grounded in reality.

Every reconciliation is fully auditable. The exception report provides visual citations that show you the unmatched transactions on both the bank statement and the GL side-by-side, making investigation quick and easy.

Visual grounding in action

00:54

Deliberate Misrepresentation: During the trial, evidence was presented showing that John Doe deliberately misrepresented his income on multiple occasions over several years. This included falsifying documents, underreporting income, and inflating deductions to lower his tax liability. Such deliberate deception demonstrates intent to evade taxes.

Pattern of Behavior: The prosecution demonstrated a consistent pattern of behavior by John Doe, spanning several years, wherein he consistently failed to report substantial portions of his income. This pattern suggested a systematic attempt to evade taxes rather than mere oversight or misunderstanding.

Concealment of Assets: Forensic accounting revealed that John Doe had taken significant steps to conceal his assets offshore, including setting up shell companies and using complex financial structures to hide income from tax authorities. Such elaborate schemes indicate a deliberate effort to evade taxes and avoid detection.

Failure to Cooperate: Throughout the investigation and trial, John Doe displayed a lack of cooperation with tax authorities. He refused to provide requested documentation, obstructed the audit process, and failed to disclose relevant financial information. This obstructionism further supported the prosecution's argument of intentional tax evasion.

Prior Warning and Ignoring Compliance

02

01

01

02

Trustworthy results,

grounded in reality.

Every reconciliation is fully auditable. The exception report provides visual citations that show you the unmatched transactions on both the bank statement and the GL side-by-side, making investigation quick and easy.

Visual grounding in action

00:54

Deliberate Misrepresentation: During the trial, evidence was presented showing that John Doe deliberately misrepresented his income on multiple occasions over several years. This included falsifying documents, underreporting income, and inflating deductions to lower his tax liability. Such deliberate deception demonstrates intent to evade taxes.

Pattern of Behavior: The prosecution demonstrated a consistent pattern of behavior by John Doe, spanning several years, wherein he consistently failed to report substantial portions of his income. This pattern suggested a systematic attempt to evade taxes rather than mere oversight or misunderstanding.

Concealment of Assets: Forensic accounting revealed that John Doe had taken significant steps to conceal his assets offshore, including setting up shell companies and using complex financial structures to hide income from tax authorities. Such elaborate schemes indicate a deliberate effort to evade taxes and avoid detection.

Failure to Cooperate: Throughout the investigation and trial, John Doe displayed a lack of cooperation with tax authorities. He refused to provide requested documentation, obstructed the audit process, and failed to disclose relevant financial information. This obstructionism further supported the prosecution's argument of intentional tax evasion.

Prior Warning and Ignoring Compliance

02

01

01

02

Trustworthy results,

grounded in reality.

Every reconciliation is fully auditable. The exception report provides visual citations that show you the unmatched transactions on both the bank statement and the GL side-by-side, making investigation quick and easy.

Visual grounding in action

00:54

Deliberate Misrepresentation: During the trial, evidence was presented showing that John Doe deliberately misrepresented his income on multiple occasions over several years. This included falsifying documents, underreporting income, and inflating deductions to lower his tax liability. Such deliberate deception demonstrates intent to evade taxes.

Pattern of Behavior: The prosecution demonstrated a consistent pattern of behavior by John Doe, spanning several years, wherein he consistently failed to report substantial portions of his income. This pattern suggested a systematic attempt to evade taxes rather than mere oversight or misunderstanding.

Concealment of Assets: Forensic accounting revealed that John Doe had taken significant steps to conceal his assets offshore, including setting up shell companies and using complex financial structures to hide income from tax authorities. Such elaborate schemes indicate a deliberate effort to evade taxes and avoid detection.

Failure to Cooperate: Throughout the investigation and trial, John Doe displayed a lack of cooperation with tax authorities. He refused to provide requested documentation, obstructed the audit process, and failed to disclose relevant financial information. This obstructionism further supported the prosecution's argument of intentional tax evasion.

Prior Warning and Ignoring Compliance

02

01

01

02

Enterprise grade security

for high-stake industries.

Your company's detailed transaction history is highly sensitive. V7 Go is built to protect this data, processing all your financial statements and reports within your secure, private environment with strict access controls.

Certifications

GDPR

SOC2

HIPAA

ISO

Safety

Custom storage

Data governance

Access-level permissions

Enterprise grade security

for high-stake industries.

Your company's detailed transaction history is highly sensitive. V7 Go is built to protect this data, processing all your financial statements and reports within your secure, private environment with strict access controls.

Certifications

GDPR

SOC2

HIPAA

ISO

Safety

Custom storage

Data governance

Access-level permissions

Enterprise grade security

for high-stake industries.

Your company's detailed transaction history is highly sensitive. V7 Go is built to protect this data, processing all your financial statements and reports within your secure, private environment with strict access controls.

Certifications

GPDR

SOC2

HIPAA

ISO

Safety

Custom storage

Data governance

Access-level permissions

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Next steps

Next steps

Ready to accelerate your financial close?

Send us an anonymized bank statement and GL export from a recent month. We'll show you how our AI agent can complete the reconciliation in minutes.

Uncover hidden liabilities

in

supplier contracts.

V7 Go transforms documents into strategic assets. 150+ enterprises are already on board:

  • Mercedes-Benz logo
    SMC  logo
    Philips logo
    Bayer Logo
    Mars Logo
    Roche logo
    Sony logo
    Alaris logo

Uncover hidden liabilities

in

supplier contracts.

V7 Go transforms documents into strategic assets. 150+ enterprises are already on board:

  • Mercedes-Benz logo
    SMC  logo
    Philips logo
    Bayer Logo
    Mars Logo
    Roche logo
    Sony logo
    Alaris logo

Answers

Answers

What you need to know about our

AI Financial Reconciliation Agent

What file formats can the agent work with?

The agent is highly flexible. It can ingest data from PDF bank statements, CSV exports from your general ledger, multi-tab Excel workbooks, and can even be connected via API to your core financial systems.

+

What file formats can the agent work with?

The agent is highly flexible. It can ingest data from PDF bank statements, CSV exports from your general ledger, multi-tab Excel workbooks, and can even be connected via API to your core financial systems.

+

What file formats can the agent work with?

The agent is highly flexible. It can ingest data from PDF bank statements, CSV exports from your general ledger, multi-tab Excel workbooks, and can even be connected via API to your core financial systems.

+

How does it handle one-to-many or many-to-one matches (e.g., one deposit for multiple invoices)?

The agent's workflow can be configured with advanced logic to handle these complex scenarios. It can be set to identify situations where a single bank transaction matches the sum of multiple GL entries, and vice versa.

+

How does it handle one-to-many or many-to-one matches (e.g., one deposit for multiple invoices)?

The agent's workflow can be configured with advanced logic to handle these complex scenarios. It can be set to identify situations where a single bank transaction matches the sum of multiple GL entries, and vice versa.

+

How does it handle one-to-many or many-to-one matches (e.g., one deposit for multiple invoices)?

The agent's workflow can be configured with advanced logic to handle these complex scenarios. It can be set to identify situations where a single bank transaction matches the sum of multiple GL entries, and vice versa.

+

Is our financial transaction data secure?

Absolutely. All your financial data is processed within your secure, private V7 Go environment. We adhere to the highest standards of data security and confidentiality, and your data is never used for any external purpose.

+

Is our financial transaction data secure?

Absolutely. All your financial data is processed within your secure, private V7 Go environment. We adhere to the highest standards of data security and confidentiality, and your data is never used for any external purpose.

+

Is our financial transaction data secure?

Absolutely. All your financial data is processed within your secure, private V7 Go environment. We adhere to the highest standards of data security and confidentiality, and your data is never used for any external purpose.

+

Can it suggest the correct journal entries for reconciling items?

Yes. Based on rules you provide (e.g., 'All transactions with the description 'Bank Fee' should be coded to GL account 6510'), the agent can suggest the appropriate adjusting journal entries for common reconciling items like bank fees or interest.

+

Can it suggest the correct journal entries for reconciling items?

Yes. Based on rules you provide (e.g., 'All transactions with the description 'Bank Fee' should be coded to GL account 6510'), the agent can suggest the appropriate adjusting journal entries for common reconciling items like bank fees or interest.

+

Can it suggest the correct journal entries for reconciling items?

Yes. Based on rules you provide (e.g., 'All transactions with the description 'Bank Fee' should be coded to GL account 6510'), the agent can suggest the appropriate adjusting journal entries for common reconciling items like bank fees or interest.

+

How is this different from the reconciliation module in our ERP?

Most ERP modules require perfectly formatted, structured data. This agent specializes in the messy part: reading unstructured PDF statements and using AI for 'fuzzy' matching, creating the clean data that can then be fed into your ERP.

+

How is this different from the reconciliation module in our ERP?

Most ERP modules require perfectly formatted, structured data. This agent specializes in the messy part: reading unstructured PDF statements and using AI for 'fuzzy' matching, creating the clean data that can then be fed into your ERP.

+

How is this different from the reconciliation module in our ERP?

Most ERP modules require perfectly formatted, structured data. This agent specializes in the messy part: reading unstructured PDF statements and using AI for 'fuzzy' matching, creating the clean data that can then be fed into your ERP.

+

How do we know the automated reconciliation is correct?

Through total transparency. The agent produces a full report showing exactly which items it matched and why. Every transaction is visually linked back to the source documents, creating a clear audit trail for your team and your external auditors.

+

How do we know the automated reconciliation is correct?

Through total transparency. The agent produces a full report showing exactly which items it matched and why. Every transaction is visually linked back to the source documents, creating a clear audit trail for your team and your external auditors.

+

How do we know the automated reconciliation is correct?

Through total transparency. The agent produces a full report showing exactly which items it matched and why. Every transaction is visually linked back to the source documents, creating a clear audit trail for your team and your external auditors.

+