90% faster triage
AI agent for Sanctions Screening Analysts
Clear your screening queue in minutes
Delegate the initial investigation of sanctions screening alerts to a specialized AI agent. It analyzes flagged SWIFT payments, cross-references sanctions lists, evaluates name matching logic, and provides clear recommendations on false positives, enabling your compliance team to process legitimate payments faster while maintaining rigorous oversight.
Ideal for
Sanctions Screening Teams
Financial Crime Compliance
Payment Operations
See AI agent for Sanctions Screening Analysts in action
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See AI agent for Sanctions Screening Analysts in action
Play video
See AI agent for Sanctions Screening Analysts in action
Play video
SWIFT Payment Alert Review
See AI agent for Sanctions Screening Analysts in action
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Time comparison
Time comparison
Traditional way
8-12 minutes per alert
With V7 Go agents
30-60 seconds
Average time saved
90%
Why V7 Go
Why V7 Go
Automated False Positive Detection
Analyzes payment details, beneficiary information, and screening logic to identify clear false positives based on name variation patterns, entity type mismatches, and geographic inconsistencies.
Automated False Positive Detection
Analyzes payment details, beneficiary information, and screening logic to identify clear false positives based on name variation patterns, entity type mismatches, and geographic inconsistencies.
Automated False Positive Detection
Analyzes payment details, beneficiary information, and screening logic to identify clear false positives based on name variation patterns, entity type mismatches, and geographic inconsistencies.
Automated False Positive Detection
Analyzes payment details, beneficiary information, and screening logic to identify clear false positives based on name variation patterns, entity type mismatches, and geographic inconsistencies.
Real-Time Sanctions List Cross-Reference
Queries current OFAC, UN, EU, and other sanctions lists in real-time to verify whether flagged entities represent genuine matches or algorithmic false positives requiring immediate clearance.
Real-Time Sanctions List Cross-Reference
Queries current OFAC, UN, EU, and other sanctions lists in real-time to verify whether flagged entities represent genuine matches or algorithmic false positives requiring immediate clearance.
Real-Time Sanctions List Cross-Reference
Queries current OFAC, UN, EU, and other sanctions lists in real-time to verify whether flagged entities represent genuine matches or algorithmic false positives requiring immediate clearance.
Real-Time Sanctions List Cross-Reference
Queries current OFAC, UN, EU, and other sanctions lists in real-time to verify whether flagged entities represent genuine matches or algorithmic false positives requiring immediate clearance.
Name Matching Intelligence
Evaluates phonetic similarities, transliteration variations, and common name patterns to distinguish between legitimate sanctions targets and innocent parties with similar names.
Name Matching Intelligence
Evaluates phonetic similarities, transliteration variations, and common name patterns to distinguish between legitimate sanctions targets and innocent parties with similar names.
Name Matching Intelligence
Evaluates phonetic similarities, transliteration variations, and common name patterns to distinguish between legitimate sanctions targets and innocent parties with similar names.
Name Matching Intelligence
Evaluates phonetic similarities, transliteration variations, and common name patterns to distinguish between legitimate sanctions targets and innocent parties with similar names.
Entity Verification and Enrichment
Cross-references beneficiary details against commercial databases and public records to validate entity legitimacy and provide additional context for risk assessment decisions.
Entity Verification and Enrichment
Cross-references beneficiary details against commercial databases and public records to validate entity legitimacy and provide additional context for risk assessment decisions.
Entity Verification and Enrichment
Cross-references beneficiary details against commercial databases and public records to validate entity legitimacy and provide additional context for risk assessment decisions.
Entity Verification and Enrichment
Cross-references beneficiary details against commercial databases and public records to validate entity legitimacy and provide additional context for risk assessment decisions.
Audit Trail Documentation
Generates complete investigation records with cited sources, decision rationale, and supporting evidence for every alert reviewed, ensuring regulatory audit readiness.
Audit Trail Documentation
Generates complete investigation records with cited sources, decision rationale, and supporting evidence for every alert reviewed, ensuring regulatory audit readiness.
Audit Trail Documentation
Generates complete investigation records with cited sources, decision rationale, and supporting evidence for every alert reviewed, ensuring regulatory audit readiness.
Audit Trail Documentation
Generates complete investigation records with cited sources, decision rationale, and supporting evidence for every alert reviewed, ensuring regulatory audit readiness.
Queue Prioritization Logic
Scores remaining alerts by risk level and complexity, directing analyst attention to high-priority cases that require human judgment while auto-clearing obvious false positives.
Queue Prioritization Logic
Scores remaining alerts by risk level and complexity, directing analyst attention to high-priority cases that require human judgment while auto-clearing obvious false positives.
Queue Prioritization Logic
Scores remaining alerts by risk level and complexity, directing analyst attention to high-priority cases that require human judgment while auto-clearing obvious false positives.
Queue Prioritization Logic
Scores remaining alerts by risk level and complexity, directing analyst attention to high-priority cases that require human judgment while auto-clearing obvious false positives.
Analyzes payment alerts and sanctions data
To deliver rapid, defensible triage decisions.
Get started
Get started
Import your files
Salesforce
,
Slack
,
Microsoft Teams
Import your files from whereever they are currently stored
All types of Finance documents supported
Once imported our system extracts and organises the essentials
Customer voices
Customer voices
Connect AI to your sanctions screening workflow.
Connect AI to your sanctions screening workflow.
Clear false positives faster while maintaining rigorous compliance.
Clear false positives faster while maintaining rigorous compliance.
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
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
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 documents.
Up to 200 pages.
Sanctions screening involves diverse document types from SWIFT messages to beneficiary verification records. This agent processes all formats, including scanned documents, multi-language payment instructions, and complex entity ownership structures.
Input types
50+ languages
Payment Messages
200 pages
Multi-modal
Document types
PDFs
SWIFT MT Messages
Tables
Structured Data
Spreadsheets
Vendor_US.xlsx
3
Supply_2023.pptx
Review_Legal.pdf
Supporting complex documents.
Up to 200 pages.
Sanctions screening involves diverse document types from SWIFT messages to beneficiary verification records. This agent processes all formats, including scanned documents, multi-language payment instructions, and complex entity ownership structures.
Input types
50+ languages
Payment Messages
200 pages
Multi-modal
Document types
PDFs
SWIFT MT Messages
Tables
Structured Data
Spreadsheets
Vendor_US.xlsx
3
Supply_2023.pptx
Review_Legal.pdf
Supporting complex documents.
Up to 200 pages.
Sanctions screening involves diverse document types from SWIFT messages to beneficiary verification records. This agent processes all formats, including scanned documents, multi-language payment instructions, and complex entity ownership structures.
Input types
50+ languages
Payment Messages
200 pages
Multi-modal
Document types
PDFs
SWIFT MT Messages
Tables
Structured Data
Spreadsheets
Vendor_US.xlsx
3
Supply_2023.pptx
Review_Legal.pdf
Reach 99% accuracy rate
through GenAI reasoning.
Sanctions compliance demands precision. The agent uses sophisticated name matching algorithms and contextual analysis to minimize both false positives and false negatives, ensuring legitimate payments clear quickly while genuine risks are escalated.
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.
Sanctions compliance demands precision. The agent uses sophisticated name matching algorithms and contextual analysis to minimize both false positives and false negatives, ensuring legitimate payments clear quickly while genuine risks are escalated.
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.
Sanctions compliance demands precision. The agent uses sophisticated name matching algorithms and contextual analysis to minimize both false positives and false negatives, ensuring legitimate payments clear quickly while genuine risks are escalated.
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.
Every triage decision is supported by visual citations linking back to the specific sanctions list entries, payment details, and verification sources consulted. This creates a complete, auditable record for regulatory examination.
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
![](data:image/svg+xml,<svg display="block" role="presentation" viewBox="0 0 198 15" xmlns="http://www.w3.org/2000/svg"><defs ><clipPath id="J0QEw1Ctk-2037569988-stroke"><use href="%23J0QEw1Ctk-2037569988"/></clipPath><path d="M 0 1 C 0 0.448 0.448 0 1 0 L 197 0 C 197.552 0 198 0.448 198 1 L 198 9 C 198 9.552 197.552 10 197 10 L 76 10 L 76 14 C 76 14.552 75.552 15 75 15 L 1 15 C 0.448 15 0 14.552 0 14 Z" id="J0QEw1Ctk-2037569988"/></defs><use fill="rgba(124, 58, 237, 0.1)" height="15px" href="%23J0QEw1Ctk-2037569988" id="J0QEw1Ctk" width="198px"/><use clip-path="url(%23J0QEw1Ctk-2037569988-stroke)" fill="transparent" href="%23J0QEw1Ctk-2037569988" stroke-dasharray="0" stroke-linecap="butt" stroke-linejoin="miter" stroke-miterlimit="4" stroke-width="1" stroke="rgb(124, 58, 237)"/></svg>)
02
01
01
02
Trustworthy results,
grounded in reality.
Every triage decision is supported by visual citations linking back to the specific sanctions list entries, payment details, and verification sources consulted. This creates a complete, auditable record for regulatory examination.
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 triage decision is supported by visual citations linking back to the specific sanctions list entries, payment details, and verification sources consulted. This creates a complete, auditable record for regulatory examination.
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.
Payment data and sanctions screening information are highly sensitive. V7 Go processes all alerts within your secure environment, maintaining strict data isolation and ensuring compliance with financial services security standards.
Certifications
GDPR
SOC2
HIPAA
ISO
Safety
Custom storage
Data governance
Access-level permissions
Enterprise grade security
for high-stake industries.
Payment data and sanctions screening information are highly sensitive. V7 Go processes all alerts within your secure environment, maintaining strict data isolation and ensuring compliance with financial services security standards.
Certifications
GDPR
SOC2
HIPAA
ISO
Safety
Custom storage
Data governance
Access-level permissions
Enterprise grade security
for high-stake industries.
Payment data and sanctions screening information are highly sensitive. V7 Go processes all alerts within your secure environment, maintaining strict data isolation and ensuring compliance with financial services security standards.
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 agent for Sanctions Screening Analysts
How does the agent determine what constitutes a false positive?
The agent applies a multi-factor analysis that includes exact name matching against current sanctions lists, evaluation of entity type consistency, geographic plausibility checks, and pattern recognition based on your institution's historical false positive data. It only auto-clears alerts that meet strict confidence thresholds.
+
How does the agent determine what constitutes a false positive?
The agent applies a multi-factor analysis that includes exact name matching against current sanctions lists, evaluation of entity type consistency, geographic plausibility checks, and pattern recognition based on your institution's historical false positive data. It only auto-clears alerts that meet strict confidence thresholds.
+
How does the agent determine what constitutes a false positive?
The agent applies a multi-factor analysis that includes exact name matching against current sanctions lists, evaluation of entity type consistency, geographic plausibility checks, and pattern recognition based on your institution's historical false positive data. It only auto-clears alerts that meet strict confidence thresholds.
+
Can this agent make final approval decisions on payments?
No. The agent performs initial triage and investigation, providing recommendations with supporting evidence. Final approval authority remains with your compliance analysts. The system is designed to accelerate their decision-making process, not replace their judgment.
+
Can this agent make final approval decisions on payments?
No. The agent performs initial triage and investigation, providing recommendations with supporting evidence. Final approval authority remains with your compliance analysts. The system is designed to accelerate their decision-making process, not replace their judgment.
+
Can this agent make final approval decisions on payments?
No. The agent performs initial triage and investigation, providing recommendations with supporting evidence. Final approval authority remains with your compliance analysts. The system is designed to accelerate their decision-making process, not replace their judgment.
+
How does it stay current with sanctions list updates?
The agent connects to your existing sanctions screening infrastructure and queries the same authoritative list sources your current system uses. It does not maintain separate lists, ensuring consistency with your compliance framework and immediate access to list updates.
+
How does it stay current with sanctions list updates?
The agent connects to your existing sanctions screening infrastructure and queries the same authoritative list sources your current system uses. It does not maintain separate lists, ensuring consistency with your compliance framework and immediate access to list updates.
+
How does it stay current with sanctions list updates?
The agent connects to your existing sanctions screening infrastructure and queries the same authoritative list sources your current system uses. It does not maintain separate lists, ensuring consistency with your compliance framework and immediate access to list updates.
+
What happens if the agent is uncertain about an alert?
Any alert that does not meet the confidence threshold for auto-clearance is flagged for analyst review with a detailed investigation summary. The agent provides all relevant context, potential risk factors, and recommended next steps to accelerate the manual review process.
+
What happens if the agent is uncertain about an alert?
Any alert that does not meet the confidence threshold for auto-clearance is flagged for analyst review with a detailed investigation summary. The agent provides all relevant context, potential risk factors, and recommended next steps to accelerate the manual review process.
+
What happens if the agent is uncertain about an alert?
Any alert that does not meet the confidence threshold for auto-clearance is flagged for analyst review with a detailed investigation summary. The agent provides all relevant context, potential risk factors, and recommended next steps to accelerate the manual review process.
+
How is this different from existing screening system filters?
Traditional screening systems use rule-based filters that often miss nuanced false positives. This agent applies contextual reasoning, evaluates multiple data sources simultaneously, and learns from your institution's historical decisions to provide more sophisticated triage than static rules allow.
+
How is this different from existing screening system filters?
Traditional screening systems use rule-based filters that often miss nuanced false positives. This agent applies contextual reasoning, evaluates multiple data sources simultaneously, and learns from your institution's historical decisions to provide more sophisticated triage than static rules allow.
+
How is this different from existing screening system filters?
Traditional screening systems use rule-based filters that often miss nuanced false positives. This agent applies contextual reasoning, evaluates multiple data sources simultaneously, and learns from your institution's historical decisions to provide more sophisticated triage than static rules allow.
+
Is every investigation decision fully auditable?
Yes. Every alert processed by the agent generates a complete audit record that includes the data sources consulted, the logic applied, the confidence score, and visual citations linking conclusions back to source documents. This creates a defensible compliance trail for regulatory examination.
+
Is every investigation decision fully auditable?
Yes. Every alert processed by the agent generates a complete audit record that includes the data sources consulted, the logic applied, the confidence score, and visual citations linking conclusions back to source documents. This creates a defensible compliance trail for regulatory examination.
+
Is every investigation decision fully auditable?
Yes. Every alert processed by the agent generates a complete audit record that includes the data sources consulted, the logic applied, the confidence score, and visual citations linking conclusions back to source documents. This creates a defensible compliance trail for regulatory examination.
+
Next steps
Next steps
Tired of your screening queue backing up legitimate payments?
Send us a sample of your recent screening alerts, and we'll show you how to resolve false positives in seconds instead of 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: