90% faster organization

AI Document Clustering Agent

Turn document chaos into organized structure

Delegate the tedious task of document organization to a specialized AI agent. It analyzes content across your entire collection, identifies relationships between documents, and automatically groups them into meaningful clusters. Your team can then focus on analysis instead of filing.

Ideal for

Deal Teams

Compliance Teams

Knowledge Management

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

See AI Document Clustering Agent 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
    Foobar logo
    ABL logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Brotherhood Mutual logo
    Mercedes-Benz logo
    Paige logo
    Roche logo
    Sony logo
    Munch Energie Logo
    Certainty Sofrware logo
    Raft logo
    Bayer Logo
    Mercedes-Benz logo
    Mercedes-Benz logo

See AI Document Clustering Agent 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
    Foobar logo
    ABL logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Brotherhood Mutual logo
    Mercedes-Benz logo
    Paige logo
    Roche logo
    Sony logo
    Munch Energie Logo
    Certainty Sofrware logo
    Raft logo
    Bayer Logo
    Mercedes-Benz logo
    Mercedes-Benz logo

See AI Document Clustering Agent in action

Play video

Data Room Organization

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

See AI Document Clustering Agent in action

Play video

Time comparison

Time comparison

Traditional way

3-4 weeks

With V7 Go agents

30-60 minutes

Average time saved

90%

Why V7 Go

Why V7 Go

Semantic Content Analysis

Reads and understands document content to identify themes, topics, and relationships. Groups documents by meaning, not just file names or metadata.

Semantic Content Analysis

Reads and understands document content to identify themes, topics, and relationships. Groups documents by meaning, not just file names or metadata.

Semantic Content Analysis

Reads and understands document content to identify themes, topics, and relationships. Groups documents by meaning, not just file names or metadata.

Semantic Content Analysis

Reads and understands document content to identify themes, topics, and relationships. Groups documents by meaning, not just file names or metadata.

Multi-Dimensional Clustering

Clusters documents across multiple dimensions simultaneously—by document type, subject matter, parties involved, and temporal relationships—creating a rich organizational structure.

Multi-Dimensional Clustering

Clusters documents across multiple dimensions simultaneously—by document type, subject matter, parties involved, and temporal relationships—creating a rich organizational structure.

Multi-Dimensional Clustering

Clusters documents across multiple dimensions simultaneously—by document type, subject matter, parties involved, and temporal relationships—creating a rich organizational structure.

Multi-Dimensional Clustering

Clusters documents across multiple dimensions simultaneously—by document type, subject matter, parties involved, and temporal relationships—creating a rich organizational structure.

Hierarchical Organization

Creates both primary clusters and subclusters, allowing teams to navigate large collections at different levels of granularity based on their needs.

Hierarchical Organization

Creates both primary clusters and subclusters, allowing teams to navigate large collections at different levels of granularity based on their needs.

Hierarchical Organization

Creates both primary clusters and subclusters, allowing teams to navigate large collections at different levels of granularity based on their needs.

Hierarchical Organization

Creates both primary clusters and subclusters, allowing teams to navigate large collections at different levels of granularity based on their needs.

Bulk Processing at Scale

Processes thousands of documents simultaneously, organizing entire data rooms, archives, or knowledge repositories in a single run.

Bulk Processing at Scale

Processes thousands of documents simultaneously, organizing entire data rooms, archives, or knowledge repositories in a single run.

Bulk Processing at Scale

Processes thousands of documents simultaneously, organizing entire data rooms, archives, or knowledge repositories in a single run.

Bulk Processing at Scale

Processes thousands of documents simultaneously, organizing entire data rooms, archives, or knowledge repositories in a single run.

Customizable Clustering Logic

Define your own clustering criteria through your Knowledge Hub. The agent adapts its grouping logic to match your firm's specific organizational needs and priorities.

Customizable Clustering Logic

Define your own clustering criteria through your Knowledge Hub. The agent adapts its grouping logic to match your firm's specific organizational needs and priorities.

Customizable Clustering Logic

Define your own clustering criteria through your Knowledge Hub. The agent adapts its grouping logic to match your firm's specific organizational needs and priorities.

Customizable Clustering Logic

Define your own clustering criteria through your Knowledge Hub. The agent adapts its grouping logic to match your firm's specific organizational needs and priorities.

Actionable Organization Output

Delivers a structured map of clusters with document assignments, relationship summaries, and recommended folder hierarchies ready for implementation.

Actionable Organization Output

Delivers a structured map of clusters with document assignments, relationship summaries, and recommended folder hierarchies ready for implementation.

Actionable Organization Output

Delivers a structured map of clusters with document assignments, relationship summaries, and recommended folder hierarchies ready for implementation.

Actionable Organization Output

Delivers a structured map of clusters with document assignments, relationship summaries, and recommended folder hierarchies ready for implementation.

Analyzes and organizes any document collection

To create a structured, navigable knowledge base.

Get started

Get started

Import your files

Microsoft Sharepoint Online

,

Google Drive

,

Notion

Import your files from whereever they are currently stored

Customer voices

Customer voices

Connect AI to your document management.

Connect AI to your document management.

Organize knowledge, accelerate decisions.

Organize knowledge, accelerate decisions.

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 collections.

Thousands of documents.

Document collections are messy. This agent handles mixed formats, inconsistent naming, poor metadata, and complex relationships. It organizes everything from small archives to massive data rooms with equal effectiveness.

Input types

Mixed Formats

Poor Metadata

Thousands of Files

Complex Relationships

Document types

PDFs

Word Docs

Spreadsheets

Images

Presentations

Vendor_US.xlsx

3

Supply_2023.pptx

Review_Legal.pdf

Supporting complex collections.

Thousands of documents.

Document collections are messy. This agent handles mixed formats, inconsistent naming, poor metadata, and complex relationships. It organizes everything from small archives to massive data rooms with equal effectiveness.

Input types

Mixed Formats

Poor Metadata

Thousands of Files

Complex Relationships

Document types

PDFs

Word Docs

Spreadsheets

Images

Presentations

Vendor_US.xlsx

3

Supply_2023.pptx

Review_Legal.pdf

Supporting complex collections.

Thousands of documents.

Document collections are messy. This agent handles mixed formats, inconsistent naming, poor metadata, and complex relationships. It organizes everything from small archives to massive data rooms with equal effectiveness.

Input types

Mixed Formats

Poor Metadata

Thousands of Files

Complex Relationships

Document types

PDFs

Word Docs

Spreadsheets

Images

Presentations

Vendor_US.xlsx

3

Supply_2023.pptx

Review_Legal.pdf

Intelligent grouping

based on content understanding.

The agent doesn't just match keywords or file names. It understands document content, context, and relationships to create meaningful clusters that reflect how your team actually thinks about the collection.

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)

Intelligent grouping

based on content understanding.

The agent doesn't just match keywords or file names. It understands document content, context, and relationships to create meaningful clusters that reflect how your team actually thinks about the collection.

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)

Intelligent grouping

based on content understanding.

The agent doesn't just match keywords or file names. It understands document content, context, and relationships to create meaningful clusters that reflect how your team actually thinks about the collection.

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)

Transparent clustering

with clear reasoning.

Every cluster assignment includes reasoning and confidence scores. Teams can understand why documents were grouped together and adjust clusters if needed, creating a transparent and auditable organization process.

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

Transparent clustering

with clear reasoning.

Every cluster assignment includes reasoning and confidence scores. Teams can understand why documents were grouped together and adjust clusters if needed, creating a transparent and auditable organization process.

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

Transparent clustering

with clear reasoning.

Every cluster assignment includes reasoning and confidence scores. Teams can understand why documents were grouped together and adjust clusters if needed, creating a transparent and auditable organization process.

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 sensitive collections.

Document collections often contain confidential information. V7 Go processes all documents within your secure environment, ensuring data privacy and compliance with your security standards. Your documents are never used for external purposes.

Certifications

GDPR

SOC2

HIPAA

ISO

Safety

Custom storage

Data governance

Access-level permissions

Enterprise grade security

for sensitive collections.

Document collections often contain confidential information. V7 Go processes all documents within your secure environment, ensuring data privacy and compliance with your security standards. Your documents are never used for external purposes.

Certifications

GDPR

SOC2

HIPAA

ISO

Safety

Custom storage

Data governance

Access-level permissions

Enterprise grade security

for sensitive collections.

Document collections often contain confidential information. V7 Go processes all documents within your secure environment, ensuring data privacy and compliance with your security standards. Your documents are never used for external purposes.

Certifications

GPDR

SOC2

HIPAA

ISO

Safety

Custom storage

Data governance

Access-level permissions

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Answers

Answers

What you need to know about our

AI Document Clustering Agent

How does the agent decide which documents belong together?

The agent analyzes document content, structure, metadata, and context to identify natural groupings. It can cluster by document type, subject matter, parties involved, time period, or custom criteria you define in your Knowledge Hub.

+

How does the agent decide which documents belong together?

The agent analyzes document content, structure, metadata, and context to identify natural groupings. It can cluster by document type, subject matter, parties involved, time period, or custom criteria you define in your Knowledge Hub.

+

How does the agent decide which documents belong together?

The agent analyzes document content, structure, metadata, and context to identify natural groupings. It can cluster by document type, subject matter, parties involved, time period, or custom criteria you define in your Knowledge Hub.

+

Can it handle mixed document types and formats?

Yes. The agent processes PDFs, Word documents, spreadsheets, images, and mixed formats within the same collection. It understands content regardless of format, making it ideal for heterogeneous data rooms and archives.

+

Can it handle mixed document types and formats?

Yes. The agent processes PDFs, Word documents, spreadsheets, images, and mixed formats within the same collection. It understands content regardless of format, making it ideal for heterogeneous data rooms and archives.

+

Can it handle mixed document types and formats?

Yes. The agent processes PDFs, Word documents, spreadsheets, images, and mixed formats within the same collection. It understands content regardless of format, making it ideal for heterogeneous data rooms and archives.

+

How many documents can it organize at once?

The agent is built for scale. It can cluster thousands of documents in a single run. Performance depends on collection size and complexity, but even large data rooms are typically organized in minutes.

+

How many documents can it organize at once?

The agent is built for scale. It can cluster thousands of documents in a single run. Performance depends on collection size and complexity, but even large data rooms are typically organized in minutes.

+

How many documents can it organize at once?

The agent is built for scale. It can cluster thousands of documents in a single run. Performance depends on collection size and complexity, but even large data rooms are typically organized in minutes.

+

What is the output format?

The agent delivers a structured clustering map showing primary clusters, subclusters, document assignments, and relationship summaries. Output can be formatted as JSON, CSV, or a visual hierarchy document for easy implementation.

+

What is the output format?

The agent delivers a structured clustering map showing primary clusters, subclusters, document assignments, and relationship summaries. Output can be formatted as JSON, CSV, or a visual hierarchy document for easy implementation.

+

What is the output format?

The agent delivers a structured clustering map showing primary clusters, subclusters, document assignments, and relationship summaries. Output can be formatted as JSON, CSV, or a visual hierarchy document for easy implementation.

+

Can we adjust the clustering after it's complete?

Yes. The clustering output is a starting point. Teams can refine clusters, merge groups, or adjust assignments based on their specific needs. The agent can also re-run with updated criteria if your organizational requirements change.

+

Can we adjust the clustering after it's complete?

Yes. The clustering output is a starting point. Teams can refine clusters, merge groups, or adjust assignments based on their specific needs. The agent can also re-run with updated criteria if your organizational requirements change.

+

Can we adjust the clustering after it's complete?

Yes. The clustering output is a starting point. Teams can refine clusters, merge groups, or adjust assignments based on their specific needs. The agent can also re-run with updated criteria if your organizational requirements change.

+

How does this integrate with our existing systems?

The clustering output can be used to organize files in SharePoint, Google Drive, or any document management system. The agent can also trigger downstream workflows to automatically move or tag documents based on cluster assignments.

+

How does this integrate with our existing systems?

The clustering output can be used to organize files in SharePoint, Google Drive, or any document management system. The agent can also trigger downstream workflows to automatically move or tag documents based on cluster assignments.

+

How does this integrate with our existing systems?

The clustering output can be used to organize files in SharePoint, Google Drive, or any document management system. The agent can also trigger downstream workflows to automatically move or tag documents based on cluster assignments.

+

Next steps

Next steps

Tired of manually organizing document collections?

Send us a sample of your unorganized documents, and we'll show you how our agent can cluster and structure them automatically.

Uncover hidden liabilities

in

supplier contracts.

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

  • Mercedes-Benz logo
    SMC  logo
    Centerline 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
    Centerline logo
    Alaris logo