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

See AI Document Clustering Agent in action
Play video

See AI Document Clustering Agent in action
Play video

See AI Document Clustering Agent in action
Play video

Data Room Organization
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
All types of Business documents supported
Once imported our system extracts and organises the essentials
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
Industrial equipment sales
Read the full story
Industrial equipment sales
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
Industrial equipment sales
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
Finance
“Whenever I think about hiring, I first try to do it in V7 Go.” Discover how HITICCO uses V7 Go agents to accelerate and enrich their prospect research.
Read the full story
Finance
The experience with V7 has been fantastic. Very customized level of support. You feel like they really care about your outcome and objectives.
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 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:
Uncover hidden liabilities
in
supplier contracts.
V7 Go transforms documents into strategic assets. 150+ enterprises are already on board: