90% faster data extraction

AI agent for Loss Run Analysts

From carrier chaos to clean data

Delegate loss run data extraction to a specialized AI agent. It reads PDF loss runs from any carrier, extracts claims history regardless of format variations, calculates loss ratios automatically, and delivers standardized data ready for your underwriting analysis.

Ideal for

Commercial Underwriters

Renewal Teams

Loss Control Analysts

  • Mercedes-Benz logo
    SMC  logo
    Mercedes-Benz logo
    Centerline logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Alaris logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Foobar logo
    ABL logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Brotherhood Mutual logo
    Mercedes-Benz logo
    Paige logo
    Roche logo
    Mercedes-Benz logo
    Sony logo
    Munch Energie Logo
    Certainty Sofrware logo
    Raft logo
    Bayer Logo
    Mercedes-Benz logo
    Mercedes-Benz logo

See AI agent for Loss Run Analysts in action

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  • Mercedes-Benz logo
    SMC  logo
    Mercedes-Benz logo
    Centerline logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Alaris logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Foobar logo
    ABL logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Brotherhood Mutual logo
    Mercedes-Benz logo
    Paige logo
    Roche logo
    Mercedes-Benz logo
    Sony logo
    Munch Energie Logo
    Certainty Sofrware logo
    Raft logo
    Bayer Logo
    Mercedes-Benz logo
    Mercedes-Benz logo

See AI agent for Loss Run Analysts in action

Play video

  • Mercedes-Benz logo
    SMC  logo
    Mercedes-Benz logo
    Centerline logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Alaris logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Foobar logo
    ABL logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Brotherhood Mutual logo
    Mercedes-Benz logo
    Paige logo
    Roche logo
    Mercedes-Benz logo
    Sony logo
    Munch Energie Logo
    Certainty Sofrware logo
    Raft logo
    Bayer Logo
    Mercedes-Benz logo
    Mercedes-Benz logo

See AI agent for Loss Run Analysts in action

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Renewal Analysis - Acme Manufacturing

  • Mercedes-Benz logo
    SMC  logo
    Mercedes-Benz logo
    Centerline logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Alaris logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Foobar logo
    ABL logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Brotherhood Mutual logo
    Mercedes-Benz logo
    Paige logo
    Roche logo
    Mercedes-Benz logo
    Sony logo
    Munch Energie Logo
    Certainty Sofrware logo
    Raft logo
    Bayer Logo
    Mercedes-Benz logo
    Mercedes-Benz logo

See AI agent for Loss Run Analysts in action

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Time comparison

Time comparison

Traditional way

45-90 minutes per loss run

With V7 Go agents

3-5 minutes

Average time saved

90%

Why V7 Go

Why V7 Go

Multi-Carrier Format Recognition

Automatically processes loss runs from any insurance carrier, adapting to different table layouts, column orders, and terminology variations without requiring manual template configuration.

Multi-Carrier Format Recognition

Automatically processes loss runs from any insurance carrier, adapting to different table layouts, column orders, and terminology variations without requiring manual template configuration.

Multi-Carrier Format Recognition

Automatically processes loss runs from any insurance carrier, adapting to different table layouts, column orders, and terminology variations without requiring manual template configuration.

Multi-Carrier Format Recognition

Automatically processes loss runs from any insurance carrier, adapting to different table layouts, column orders, and terminology variations without requiring manual template configuration.

Automated Loss Ratio Calculation

Extracts incurred amounts, paid losses, and premium data to calculate loss ratios by policy year, coverage type, and claim category, eliminating manual spreadsheet formulas and calculation errors.

Automated Loss Ratio Calculation

Extracts incurred amounts, paid losses, and premium data to calculate loss ratios by policy year, coverage type, and claim category, eliminating manual spreadsheet formulas and calculation errors.

Automated Loss Ratio Calculation

Extracts incurred amounts, paid losses, and premium data to calculate loss ratios by policy year, coverage type, and claim category, eliminating manual spreadsheet formulas and calculation errors.

Automated Loss Ratio Calculation

Extracts incurred amounts, paid losses, and premium data to calculate loss ratios by policy year, coverage type, and claim category, eliminating manual spreadsheet formulas and calculation errors.

Claims Frequency Analysis

Identifies claim frequency patterns across policy periods, flagging unusual spikes or trends that require underwriter attention during renewal evaluation.

Claims Frequency Analysis

Identifies claim frequency patterns across policy periods, flagging unusual spikes or trends that require underwriter attention during renewal evaluation.

Claims Frequency Analysis

Identifies claim frequency patterns across policy periods, flagging unusual spikes or trends that require underwriter attention during renewal evaluation.

Claims Frequency Analysis

Identifies claim frequency patterns across policy periods, flagging unusual spikes or trends that require underwriter attention during renewal evaluation.

Standardized Data Output

Converts inconsistent carrier formats into a uniform data structure, enabling direct comparison across multiple insureds and integration with your underwriting management system.

Standardized Data Output

Converts inconsistent carrier formats into a uniform data structure, enabling direct comparison across multiple insureds and integration with your underwriting management system.

Standardized Data Output

Converts inconsistent carrier formats into a uniform data structure, enabling direct comparison across multiple insureds and integration with your underwriting management system.

Standardized Data Output

Converts inconsistent carrier formats into a uniform data structure, enabling direct comparison across multiple insureds and integration with your underwriting management system.

Large Claim Identification

Automatically flags claims exceeding specified thresholds, highlighting catastrophic losses and severity trends that impact pricing decisions and risk appetite.

Large Claim Identification

Automatically flags claims exceeding specified thresholds, highlighting catastrophic losses and severity trends that impact pricing decisions and risk appetite.

Large Claim Identification

Automatically flags claims exceeding specified thresholds, highlighting catastrophic losses and severity trends that impact pricing decisions and risk appetite.

Large Claim Identification

Automatically flags claims exceeding specified thresholds, highlighting catastrophic losses and severity trends that impact pricing decisions and risk appetite.

Verifiable Data Extraction

Every extracted claim amount, date, and description is visually linked back to its exact location in the source PDF, providing a complete audit trail for underwriting file documentation.

Verifiable Data Extraction

Every extracted claim amount, date, and description is visually linked back to its exact location in the source PDF, providing a complete audit trail for underwriting file documentation.

Verifiable Data Extraction

Every extracted claim amount, date, and description is visually linked back to its exact location in the source PDF, providing a complete audit trail for underwriting file documentation.

Verifiable Data Extraction

Every extracted claim amount, date, and description is visually linked back to its exact location in the source PDF, providing a complete audit trail for underwriting file documentation.

Customer voices

Customer voices

Connect AI to your underwriting workflow.

Connect AI to your underwriting workflow.

Turn carrier chaos into clean, comparable claims data.

Turn carrier chaos into clean, comparable claims data.

Finance

Legal

Insurance

Tax

Real Estate

Finance

Legal

Insurance

Tax

Real Estate

Finance

Legal

Insurance

Tax

Real Estate

Customer Voices

Industrial equipment sales

We are looking for V7 Go and AI in general to be the beating heart of our company and our growth. It will make us more productive as a company, liaising with customers, automating tasks, even finding new work.

Read the full story

Industrial equipment sales

We are looking for V7 Go and AI in general to be the beating heart of our company and our growth. It will make us more productive as a company, liaising with customers, automating tasks, even finding new work.

Read the full story

Insurance

We have six assessors. Before V7 Go, each would process around 15 claims a day, about 90 in total. With V7 Go, we’re expecting that to rise to around 20 claims per assessor, which adds up to an extra 30 claims a day. That’s the equivalent of two additional full-time assessors. Beyond the cost savings, there’s real reputational gains from fewer errors and faster turnaround times.

Read the full story

Insurance

We have six assessors. Before V7 Go, each would process around 15 claims a day, about 90 in total. With V7 Go, we’re expecting that to rise to around 20 claims per assessor, which adds up to an extra 30 claims a day. That’s the equivalent of two additional full-time assessors. Beyond the cost savings, there’s real reputational gains from fewer errors and faster turnaround times.

Read the full story

Real Estate

Prior to V7, people using the software were manually inputting data. Now it’s so much faster because it just reads it for them. On average, it saves our customers 45 minutes to an hour of work, and it’s more accurate.

Read the full story

Real Estate

Prior to V7, people using the software were manually inputting data. Now it’s so much faster because it just reads it for them. On average, it saves our customers 45 minutes to an hour of work, and it’s more accurate.

Read the full story

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.

Loss runs come in countless formats from different carriers. This agent handles everything from clean digital PDFs to scanned faxes with complex multi-page tables, extracting claims data regardless of layout variations or document quality.

Input types

50+ languages

Low-Quality Scans

200 pages

Multi-modal

Document types

PDFs

Scanned Documents

Complex Tables

Multi-Page Layouts

Spreadsheets

Vendor_US.xlsx

3

Supply_2023.pptx

Review_Legal.pdf

Supporting complex documents.

Up to 200 pages.

Loss runs come in countless formats from different carriers. This agent handles everything from clean digital PDFs to scanned faxes with complex multi-page tables, extracting claims data regardless of layout variations or document quality.

Input types

50+ languages

Low-Quality Scans

200 pages

Multi-modal

Document types

PDFs

Scanned Documents

Complex Tables

Multi-Page Layouts

Spreadsheets

Vendor_US.xlsx

3

Supply_2023.pptx

Review_Legal.pdf

Supporting complex documents.

Up to 200 pages.

Loss runs come in countless formats from different carriers. This agent handles everything from clean digital PDFs to scanned faxes with complex multi-page tables, extracting claims data regardless of layout variations or document quality.

Input types

50+ languages

Low-Quality Scans

200 pages

Multi-modal

Document types

PDFs

Scanned Documents

Complex Tables

Multi-Page Layouts

Spreadsheets

Vendor_US.xlsx

3

Supply_2023.pptx

Review_Legal.pdf

Reach 99% accuracy rate

through GenAI reasoning.

Pricing decisions depend on accurate loss data. The agent uses multi-step validation to ensure claim amounts, dates, and calculations are extracted with precision, eliminating the manual errors that can distort loss ratios and renewal pricing.

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

Min

Low

Mid

High

AI Citations

Inputs

Set a prompt (Press @ to mention an input)

Reach 99% accuracy rate

through GenAI reasoning.

Pricing decisions depend on accurate loss data. The agent uses multi-step validation to ensure claim amounts, dates, and calculations are extracted with precision, eliminating the manual errors that can distort loss ratios and renewal pricing.

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

Min

Low

Mid

High

AI Citations

Inputs

Set a prompt (Press @ to mention an input)

Reach 99% accuracy rate

through GenAI reasoning.

Pricing decisions depend on accurate loss data. The agent uses multi-step validation to ensure claim amounts, dates, and calculations are extracted with precision, eliminating the manual errors that can distort loss ratios and renewal pricing.

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

Min

Low

Mid

High

AI Citations

Inputs

Set a prompt (Press @ to mention an input)

Trustworthy results,

grounded in reality.

Build confidence in your underwriting decisions. Every extracted claim amount and date is visually linked to its exact location in the source loss run, providing instant verification and a complete audit trail for file documentation.

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.

Build confidence in your underwriting decisions. Every extracted claim amount and date is visually linked to its exact location in the source loss run, providing instant verification and a complete audit trail for file documentation.

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.

Build confidence in your underwriting decisions. Every extracted claim amount and date is visually linked to its exact location in the source loss run, providing instant verification and a complete audit trail for file documentation.

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.

Loss runs contain sensitive claims information and insured data. V7 Go processes these documents within your secure environment, ensuring confidentiality and compliance with insurance data protection standards.

Certifications

GDPR

SOC2

HIPAA

ISO

Safety

Custom storage

Data governance

Access-level permissions

Enterprise grade security

for high-stake industries.

Loss runs contain sensitive claims information and insured data. V7 Go processes these documents within your secure environment, ensuring confidentiality and compliance with insurance data protection standards.

Certifications

GDPR

SOC2

HIPAA

ISO

Safety

Custom storage

Data governance

Access-level permissions

Enterprise grade security

for high-stake industries.

Loss runs contain sensitive claims information and insured data. V7 Go processes these documents within your secure environment, ensuring confidentiality and compliance with insurance data protection standards.

Certifications

GPDR

SOC2

HIPAA

ISO

Safety

Custom storage

Data governance

Access-level permissions

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Automatically triages incoming claims by severity and fraud risk, then routes them to the right team.

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Instantly analyzes insurance policies to extract coverages, limits, exclusions, and endorsements.

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Automates claims intake by extracting data from FNOL submissions, forms, and supporting documents.

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Answers

Answers

What you need to know about our

AI agent for Loss Run Analysts

How does it handle different carrier formats?

The agent uses advanced table recognition to identify claims data regardless of carrier-specific formatting. It understands semantic relationships between columns, so it correctly extracts data even when carriers use different column orders, headers, or terminology for the same information.

+

How does it handle different carrier formats?

The agent uses advanced table recognition to identify claims data regardless of carrier-specific formatting. It understands semantic relationships between columns, so it correctly extracts data even when carriers use different column orders, headers, or terminology for the same information.

+

How does it handle different carrier formats?

The agent uses advanced table recognition to identify claims data regardless of carrier-specific formatting. It understands semantic relationships between columns, so it correctly extracts data even when carriers use different column orders, headers, or terminology for the same information.

+

Can it process multi-year loss runs?

Yes. The agent automatically segments claims by policy year, even when carriers present data in complex multi-year formats with varying levels of detail. It maintains the temporal structure needed for accurate loss development analysis.

+

Can it process multi-year loss runs?

Yes. The agent automatically segments claims by policy year, even when carriers present data in complex multi-year formats with varying levels of detail. It maintains the temporal structure needed for accurate loss development analysis.

+

Can it process multi-year loss runs?

Yes. The agent automatically segments claims by policy year, even when carriers present data in complex multi-year formats with varying levels of detail. It maintains the temporal structure needed for accurate loss development analysis.

+

What happens with scanned or low-quality PDFs?

The agent includes advanced OCR capabilities specifically tuned for insurance documents. It can extract data from scanned loss runs, faxed documents, and low-resolution PDFs that would be unreadable by standard extraction tools.

+

What happens with scanned or low-quality PDFs?

The agent includes advanced OCR capabilities specifically tuned for insurance documents. It can extract data from scanned loss runs, faxed documents, and low-resolution PDFs that would be unreadable by standard extraction tools.

+

What happens with scanned or low-quality PDFs?

The agent includes advanced OCR capabilities specifically tuned for insurance documents. It can extract data from scanned loss runs, faxed documents, and low-resolution PDFs that would be unreadable by standard extraction tools.

+

How accurate is the loss ratio calculation?

The agent achieves high accuracy by using multi-step validation. It cross-references extracted premium amounts with incurred losses, validates date ranges, and flags any mathematical inconsistencies for review before finalizing calculations.

+

How accurate is the loss ratio calculation?

The agent achieves high accuracy by using multi-step validation. It cross-references extracted premium amounts with incurred losses, validates date ranges, and flags any mathematical inconsistencies for review before finalizing calculations.

+

How accurate is the loss ratio calculation?

The agent achieves high accuracy by using multi-step validation. It cross-references extracted premium amounts with incurred losses, validates date ranges, and flags any mathematical inconsistencies for review before finalizing calculations.

+

Can it identify specific claim types or causes?

Yes. The agent extracts claim descriptions and categorizes them by type when that information is present in the loss run. It can identify patterns like slip-and-fall claims, auto liability, or property damage to support risk assessment.

+

Can it identify specific claim types or causes?

Yes. The agent extracts claim descriptions and categorizes them by type when that information is present in the loss run. It can identify patterns like slip-and-fall claims, auto liability, or property damage to support risk assessment.

+

Can it identify specific claim types or causes?

Yes. The agent extracts claim descriptions and categorizes them by type when that information is present in the loss run. It can identify patterns like slip-and-fall claims, auto liability, or property damage to support risk assessment.

+

What format is the final output?

The agent delivers structured data in Excel or CSV format, with each claim as a separate row and standardized columns for date of loss, claim amount, status, and other key fields. This format integrates directly with most underwriting systems.

+

What format is the final output?

The agent delivers structured data in Excel or CSV format, with each claim as a separate row and standardized columns for date of loss, claim amount, status, and other key fields. This format integrates directly with most underwriting systems.

+

What format is the final output?

The agent delivers structured data in Excel or CSV format, with each claim as a separate row and standardized columns for date of loss, claim amount, status, and other key fields. This format integrates directly with most underwriting systems.

+

Next steps

Next steps

Still manually typing claims data into spreadsheets?

Send us a few loss runs from different carriers, and we'll show you how our AI agent can standardize them all in minutes.

Uncover hidden liabilities

in

supplier contracts.

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

Uncover hidden liabilities

in

supplier contracts.

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