2026
Meet Us at Chicago RIMS' New Year Kick Off Party
You Can’t Control Attacks.
You Can Control Data Spread.
You Can’t Control Attacks.
You Can Control Data Spread.
You Can’t Control Attacks.
You Can Control Data Spread.
Attacks are inevitable. The impact depends on how widely PII and PHI have been exposed.
GenAnonymize, InsOps' AI platform eliminates PII and PHI data exposure by applying non-reversible masking inside your environment, so exposed data cannot be re-identified even when a breach. Meet us at Chicago RIMS to learn more about the solution.
Why This Matters
PII and PHI exposure is at an all-time high
Personal data is now one of the most valuable assets in the global economy, with the market projected to exceed $500 billion by 2033.
As reliance on data grows, so does exposure. In insurance, 42 of the top 150 insurers have publicly reported at least one data breach, and the average cost of a breach is nearing $5 million.
For insurers, data privacy is no longer a security concern alone. It has become a core operational requirement for managing risk, trust, and regulatory expectations.
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$512 Billion
The projected value of the global data market by 2033
Real data is used in lower environments
The projected value of the global data market by 2033
Real data is used in lower environments
The projected value of the global data market by 2033
Stage 1
Real data is used in lower environments
The projected value of the global data market by 2033
Comprehensive Consultation
Project Roadmap
28%
Large insurers experienced at least one publicly reported breach, which was higher than the overall breach rate for the S&P 500
Manual masking does not hold up
Large insurers experienced at least one publicly reported breach, which was higher than the overall breach rate for the S&P 500
Manual masking does not hold up
Large insurers experienced at least one publicly reported breach, which was higher than the overall breach rate for the S&P 500
Stage 2
Manual masking does not hold up
Large insurers experienced at least one publicly reported breach, which was higher than the overall breach rate for the S&P 500
$4.4 Million
The average cost of a data breach.
Generic tools miss insurance context
The average cost of a data breach.
Generic tools miss insurance context
The average cost of a data breach.
Generic tools miss insurance context
The average cost of a data breach.
The Problem with Existing Solutions
Existing Data Privacy Solutions are Good but not Good Enough.
Masking protects only the original fields, leaving derived or copied data unprotected.
Masking protects only the original fields, leaving derived or copied data unprotected.
Pseudonymization can be reversed, allowing identities to be reconstructed if mappings are accessed.
Protection does not persist once data is copied or shared, creating exposure outside the original system.
The Solution
GenAnonymize was Designed for Dynamic Insurance Data
GenAnonymize was Designed for Dynamic Insurance Data
GenAnonymize is built for data that gets copied, combined, and shared, ensuring it remains non-identifiable even after it is used elsewhere.
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What You'll Get in this Live Demo
See How Insurers Protect PII and PHI and eliminate exposure
Meet the InsOps team to understand how insurers apply non-reversible masking to sensitive data inside their environment, reducing exposure while analytics, testing, and daily operations continue uninterrupted.
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Identify Sensitive Data Automatically
PII and PHI are detected across policy, claims, billing, and partner datasets using insurance-specific intelligence, without relying on manual tagging or static rules.
Identify Sensitive Data Automatically
PII and PHI are detected across policy, claims, billing, and partner datasets using insurance-specific intelligence, without relying on manual tagging or static rules.
Identify Sensitive Data Automatically
PII and PHI are detected across policy, claims, billing, and partner datasets using insurance-specific intelligence, without relying on manual tagging or static rules.
Identify Sensitive Data Automatically
PII and PHI are detected across policy, claims, billing, and partner datasets using insurance-specific intelligence, without relying on manual tagging or static rules.
Apply Privacy That Supports Compliance
Sensitive fields are masked in a way that supports regulatory expectations such as GDPR, GLBA, and HIPAA, helping reduce audit risk without introducing new tools or processes.
Apply Privacy That Supports Compliance
Sensitive fields are masked in a way that supports regulatory expectations such as GDPR, GLBA, and HIPAA, helping reduce audit risk without introducing new tools or processes.
Apply Privacy That Supports Compliance
Sensitive fields are masked in a way that supports regulatory expectations such as GDPR, GLBA, and HIPAA, helping reduce audit risk without introducing new tools or processes.
Apply Privacy That Supports Compliance
Sensitive fields are masked in a way that supports regulatory expectations such as GDPR, GLBA, and HIPAA, helping reduce audit risk without introducing new tools or processes.
Protect Data at the Source
Data is protected where it is created and used, without exporting or copying sensitive information to external systems.
Protect Data at the Source
Data is protected where it is created and used, without exporting or copying sensitive information to external systems.
Protect Data at the Source
Data is protected where it is created and used, without exporting or copying sensitive information to external systems.
Protect Data at the Source
Data is protected where it is created and used, without exporting or copying sensitive information to external systems.
Keep Data Usable for Daily Work
Masked data retains structure and context, allowing teams to continue analytics, testing, reporting, and operational work without disruption.
Keep Data Usable for Daily Work
Masked data retains structure and context, allowing teams to continue analytics, testing, reporting, and operational work without disruption.
Keep Data Usable for Daily Work
Masked data retains structure and context, allowing teams to continue analytics, testing, reporting, and operational work without disruption.
Keep Data Usable for Daily Work
Masked data retains structure and context, allowing teams to continue analytics, testing, reporting, and operational work without disruption.
Maintain Protection as Data Changes
As schemas evolve and new fields appear, protection adapts automatically, preventing gaps as data is copied, combined, or reused.
Maintain Protection as Data Changes
As schemas evolve and new fields appear, protection adapts automatically, preventing gaps as data is copied, combined, or reused.
Maintain Protection as Data Changes
As schemas evolve and new fields appear, protection adapts automatically, preventing gaps as data is copied, combined, or reused.
Maintain Protection as Data Changes
As schemas evolve and new fields appear, protection adapts automatically, preventing gaps as data is copied, combined, or reused.
Track Protection as Data Evolves
Continuously monitors anonymization coverage and flags newly introduced sensitive fields as systems change.
Track Protection as Data Evolves
Continuously monitors anonymization coverage and flags newly introduced sensitive fields as systems change.
Track Protection as Data Evolves
Continuously monitors anonymization coverage and flags newly introduced sensitive fields as systems change.
Track Protection as Data Evolves
Continuously monitors anonymization coverage and flags newly introduced sensitive fields as systems change.
Testimonial
What Our Insurance Partners Say
Hear how insurers accelerated data workflows, improved accuracy, and modernized operations with InsOps.
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FAQ
Frequently
Asked Questions
Have questions? Our FAQ section has you covered with
quick answers to the most common inquiries.
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What is GenAnonymize?
How does GenAnonymize secure PII & PHI data?
Does GenAnonymize work in real time?
What types of sensitive data can GenAnonymize detect?
Will pseudonymization impact data quality or usefulness?
Do we need to write scripts or manage rules?
Is GenAnonymize compliant with regulatory requirements?
Does any data leave our environment while using GenAnonymize?
Can pseudonymization methods be customized?
What is GenAnonymize?
How does GenAnonymize secure PII & PHI data?
Does GenAnonymize work in real time?
What types of sensitive data can GenAnonymize detect?
Will pseudonymization impact data quality or usefulness?
Do we need to write scripts or manage rules?
Is GenAnonymize compliant with regulatory requirements?
Does any data leave our environment while using GenAnonymize?
Can pseudonymization methods be customized?
What is GenAnonymize?
How does GenAnonymize secure PII & PHI data?
Does GenAnonymize work in real time?
What types of sensitive data can GenAnonymize detect?
Will pseudonymization impact data quality or usefulness?
Do we need to write scripts or manage rules?
Is GenAnonymize compliant with regulatory requirements?
Does any data leave our environment while using GenAnonymize?
Can pseudonymization methods be customized?
What is GenAnonymize?
How does GenAnonymize secure PII & PHI data?
Does GenAnonymize work in real time?
What types of sensitive data can GenAnonymize detect?
Will pseudonymization impact data quality or usefulness?
Do we need to write scripts or manage rules?
Is GenAnonymize compliant with regulatory requirements?
Does any data leave our environment while using GenAnonymize?
Can pseudonymization methods be customized?
Join Us Now
Every Insurer We Work With
Moves Faster and Operates Smarter.
Join us and turn complex data challenges into streamlined, automated operations with the help of our Insurance-trained SLM
Join Us Now
Each Project, Our
Design is Great.
Join us and turn complex data challenges into streamlined, automated operations with the help of our Insurance-trained SLM
Join Us Now
Every Insurer We Work With
Moves Faster and Operates Smarter.
Join us and turn complex data challenges into streamlined, automated operations with the help of our Insurance-trained SLM
Join Us Now
Every Insurer We Work With
Moves Faster and Operates Smarter.
Join us and turn complex data challenges into streamlined, automated operations with the help of our Insurance-trained SLM