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Cybersecurity Exposure.
Quantified by AI.
Measured in EBITDA.

Your organization runs 50+ security tools. Each one speaks a different language. None of them can tell you what your EBITDA exposure actually is.

The Thrivaca AI Engine translates fragmented security data into actuarially validated financial metrics — so every dollar of exposure is measured against EBITDA impact, every remediation is prioritized by financial return, and every stakeholder works from one actuarially validated number.


See How It Works →

 

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Thrivaca AI Engine Executive Dashboard

The Cyber Exposure You Can't See Is The Exposure Eating Your EBITDA.

Most organizations cannot quantify cyber exposure in financial terms—
leaving leaders unable to measure EBITDA risk or prioritize mitigation effectively.

THE FRAGMENTATION PROBLEM

50+ security tools generating conflicting data in incompatible formats.

No normalization. No unified view.

Your SIEM aggregates events but cannot normalize risk or quantify financial exposure.

THE COMMUNICATION GAP

A documented 12–30 percentage point gap between what CISOs report and what boards understand.

Heat maps and traffic-light scoring cannot answer the board’s real question: “How much EBITDA is at risk?”

Without that answer, fiduciary decisions are made on incomplete data.

THE MEASUREMENT FAILURE

Legacy CRQ approaches (FAIR, Monte Carlo, VaR) depend on professional opinion and subjective judgment.

They require clean data that doesn’t exist. They produce ranges, not actuarial metrics.

At enterprise scale, they break. Organizations consistently underestimate true EBITDA exposure by 89–400%.

 These aren’t process problems. They are data problems at a scale that only AI can solve.
That’s why the ArxNimbus Thrivaca AI Engine exists —
and why it was built on actuarial science, not professional opinion. 

One Actuarial AI Engine. Two Ways to Quantify Cyber Exposure.

The Thrivaca AI Engine performs dual translation — AI-driven machine-to-machine normalization of fragmented security data, and machine-to-human conversion into EBITDA-grade financial exposure metrics. The same patented actuarial AI engine built on NIST-designed methodology and trusted by insurers covering 35% of the S&P 500.

The output: current EBITDA at risk, projected EBITDA exposure after controls, and ROI for every remediation dollar.

Two products.
Same engine.
Different data intake modes.

Choose based on your needs:  

Need a point-in-time exposure assessment? Start with CORE.
Need continuous visibility across your full security stack? Start with UNIFY.
Both use the same patented actuarial engine. Both deliver financial exposure in dollars. 

ThrivacaCORE™
Periodic Cyber Exposure Assessment

ThrivacaUNIFY™
 Continuous Cyber Exposure Intelligence 

Best for:

  • Organizations needing point-in-time exposure quantification.

  • Insurance underwriting portfolios.

  • M&A due diligence.

  • Annual/quarterly risk assessments. Benchmarking against 3,500+ peers. 

Best for:

  • Enterprises requiring continuous visibility across their full security stack.

  • CISOs managing 50+ tools.

  • Organizations with SBOM/RBOM/AIBOM compliance requirements. Continuous CTEM programs. 

How it works:

  • External scans + customer-provided data. The Thrivaca AI Engine builds a comprehensive Risk Profile using external attack surface analysis, customer financials, and actuarial models — translating technical findings directly into EBITDA exposure metrics.

  • Initial profile with full financial quantification available within 5 business days.

How it works:

  • API integration with your existing tools. ThrivacaUNIFY connects directly to Qualys, Wiz, CrowdStrike, Armis, Snyk, Tenable, ServiceNow, and 50+ platforms.

  • AI-driven normalization unifies fragmented CVEs, assets, and severity data through knowledge graph architecture into one actuarial-grade EBITDA exposure model — continuously. 

     

Data Sources:

  • External scans (automated), customer financial data, security documentation, risk registers, audit reports, penetration testing results, and SME attestation. 

     

Data Sources:

  • SIEM, vulnerability management, endpoint, cloud, asset management, SBOM/RBOM/AIBOM generation, CI/CD pipelines, container registries, and governance tools. 

Key outputs:

  • T-Score™ (0–1000 risk positioning).

  • EBITDA at Risk.

  • Net Risk Exposure.

  • Remediated Risk value.

  • ROI per remediation dollar.

  • 650+ NIST-approved remediation playbooks.

  • Digital twin scenario modeling.  

Key outputs:

  • Unified Threat Exposure Metric across all tools.

  • Continuous financial exposure trending.

  • Automated SBOM/RBOM generation.

  • AI operational assurance (AIBOM).

  • Left-of-Boom mitigation across complete SDLC.

  • Real-time deviation detection. 

Unique capabilities:

  • 3,500+ company benchmarking library across 580 industries.

  • Cyber Efficiency Index ($10–$144 risk reduction per $1 spent).

  • M&A risk comparison.

  • Insurance optimization modeling. 

     

Unique capabilities:

  • Only CTEM platform with actuarial financial quantification.

  • Proprietary RBOM (no other platform offers this).

  • Software supply chain + AI operational assurance in one platform.

  • 600,000+ endpoint scale. 

Delivery:

  • Periodic (quarterly/annual).

  • SaaS platform with optional on-premise.

  • Initial Risk Profile in 5 business days.

Delivery:

  • Continuous.

  • SaaS or on-premise integration.

  • Weeks, not months to deploy.

Starting investment:

  • $20K–$140K/year (enterprise).

  • $275–$320K/year (insurance underwriting). 

Starting investment:

  • Subscription-based. Contact for pricing. 

EXPLORE ThrivacaCORE →

EXPLORE ThrivacaUNIFY →

 

What Organizations Use Cyber Exposure Intelligence For.

  • AI-driven identification of the highest-impact areas for risk reduction based on EBITDA exposure, not technical severity.

  • The Cyber Efficiency Index reveals whether security spending produces measurable EBITDA return ($10–$144 per dollar invested) or diminishing returns.

  • AI-driven identification of the highest-impact areas for risk reduction based on EBITDA exposure, not technical severity.

  • The Cyber Efficiency Index reveals whether security spending produces measurable EBITDA return ($10–$144 per dollar invested) or diminishing returns.

  • AI-generated independent Risk Profiles for both acquiring and target companies.

  • Quantifies unfunded EBITDA liabilities that affect deal valuation — some M&A deals have lost up to $100M from undetected cyber exposure.

  • Digital twin modeling shows post-acquisition EBITDA impact before the deal closes.

 

  • Maps risk quantification to NIST, ISO 27001, CMMC, HIPAA, PCI DSS with 650+ remediation playbooks.

  • Data-driven, auditable evidence that replaces checkbox compliance.

  • Supports SEC cyber disclosure requirements.

 

  • AI-driven actuarial quantification of actual EBITDA exposure to determine appropriate coverage, deductibles, and policy structures.

  • Identifies where self-remediation delivers better EBITDA return than insurance transfer.

  • Prevents underinsurance disasters — UnitedHealthcare held only $100M coverage against $6.3B in actual losses.

 Automated SBOM generation, proprietary RBOM tracking across dev/QA/staging/production, and CISA KEV scoring.

Continuous monitoring of software components with financial impact quantification. (UNIFY) 

 

Measured Cyber Exposure Outcomes. Not Marketing Claims.

Every result below was produced by the Thrivaca AI Engine — the same actuarial AI architecture validated by insurers, the Department of Defense, and leading academic institutions.

These are EBITDA outcomes, not projections.

HEALTHCARE DIAGNOSTICS PROVIDER

EBITDA at risk reduced from 18.6% to 4.98% (−73%).

 

97% of cybersecurity exposure eliminated over 5 years.

 

~$7M in annual earnings protected.

 

$145 in EBITDA exposure reduction per $1 invested.

 

CEO: “This is the first time I’ve felt I can be comfortable.”

GLOBAL FINANCIAL SERVICES FIRM

$381M in actual EBITDA exposure discovered vs.

 

$75M estimated (408% variance).

 

$25M in previously unrecognized costs recovered in Year 1.

 

EBITDA risk carrying cost reduced 8.2% in first year.

 

Transformed from opinion-based risk management to AI-driven EBITDA governance.

$170B GLOBAL BIO-PHARMA CORPORATION

Replaced a $300K consulting engagement that produced opinion-driven results.

 

Discovered 89% underestimation of data breach risk and 98% miscalculation of ransomware losses.

 

Quantified exposure in dollar terms for the first time.

 

Identified unfunded liabilities and insurance gaps invisible to prior assessments.

Checkmark
97% Risk Eliminated

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408% Hidden Exposure Eliminated

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$145 ROI Per $1

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Within 7% of Actual Loss Outcomes

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3,500+ Companies Benchmarked

What Changes for Your Organization.

CISOs & SECURITY TEAMS

One AI-driven unified exposure metric across every tool in your stack — expressed in EBITDA impact, not vendor scores.

AI-optimized remediation roadmaps with 650+ NIST-approved playbooks.

Complete SBOM/RBOM visibility.

Stop managing alerts — start managing EBITDA exposure.

 

CFOs & FINANCE

Cyber exposure quantified in EBITDA terms — comparable, accountable, and financially defensible.

Current EBITDA at risk, projected EBITDA after controls, and every remediation dollar tracked against EBITDA return.

Leading organizations achieve $10–$144 in EBITDA exposure reduction per $1 invested.

 

BOARDS & C-SUITE

Two defensible numbers: current EBITDA at risk and projected EBITDA exposure after controls.

AI-generated actuarial governance metrics that replace heat maps with financial precision.

30-minute quarterly board reviews demonstrating measurable EBITDA protection.

 

LEGAL & COMPLIANCE

Audit-ready, NIST-aligned documentation that withstands regulatory and litigation scrutiny.

Tracks organizational risk progression over time.

Supports both defense and insurance recovery arguments.

  

INSURANCE & RISK TRANSFER

Quantified exposure modeling to optimize coverage and strengthen premium negotiations.

Identifies where self-remediation is more cost-effective than insurance transfer. 

 

Simulate Cyber Exposure Before You Spend.

The ArxNimbus Thrivaca AI Engine creates an AI-powered digital twin
of your organization’s entire exposure landscape.
 
Model the EBITDA impact of any strategic decision — M&A, cloud migration, digital transformation, budget reallocation — against your actual exposure data before committing a single dollar.
 
See exactly how each scenario changes your EBITDA at risk, your net exposure, and your remediation ROI.
 
  • One healthcare organization used the AI-powered digital twin to evaluate seven potential improvement scenarios before committing resources — reducing EBITDA at risk from 18.6% to 4.98%.
  • A financial services firm discovered $381M in hidden EBITDA exposure — 408% more than estimated. The digital twin turns every strategic decision into a measured EBITDA investment.
 
SEE DIGITAL TWIN IN ACTION →

AI-Powered EBITDA Intelligence From Your Existing Tools.

The Thrivaca AI Engine integrates with your existing security stack — no replacement required.
AI-driven normalization transforms every tool’s output into EBITDA exposure intelligence.
Your prior security investments become more valuable the moment they connect to the engine.

How Much EBITDA Exposure Are You Carrying?

Most organizations discover they’re underestimating actual EBITDA exposure by 89–400%.

A 30-minute executive briefing will show you where your hidden exposure is —
and what it’s costing your EBITDA every quarter you don’t measure it.

 

REQUEST AN EXECUTIVE BRIEFING → SEE THE AI ENGINE IN ACTION →