Calculate Your AI Governance ROI.
Uncontrolled AI in regulated environments creates measurable financial exposure. Arbitex delivers ROI on three dimensions — before you ever calculate the cost of a breach.
The business case for AI governance.
Most enterprise buying decisions involve all three pillars. Lead with the one most relevant to your audience — the others are additive.
Breach costs and regulatory fines dwarf governance infrastructure.
A single data breach in healthcare averages $9.77M. In financial services: $6.08M. A single EU AI Act violation can reach €35M or 7% of global annual turnover.
Breach cost data: IBM Cost of a Data Breach Report 2024. Fine ranges: EU AI Act Article 99 (Regulation (EU) 2024/1689). Actual fines depend on specific circumstances, cooperation, and jurisdiction.
Building internally takes a dedicated engineering team and 12+ months.
At fully-loaded engineering costs, that is $1.25M–$1.9M per year — before maintenance, compliance updates, and provider API changes. Arbitex deploys in days.
Build cost based on industry salary benchmarks for senior engineering roles. Estimate assumes 5 FTE at $250K–$380K fully loaded. Your numbers may vary.
Track every token. Control every dollar.
Arbitex tracks token consumption per provider, per department, and per user. Set budget caps and usage quotas to prevent cost overruns — with real-time alerts before limits are reached.
Cost analytics cover all routed providers. Budget enforcement applies at the organization, department, and individual user level.
Estimate your exposure and savings.
Enter your organization profile to see a conservative estimate of your AI governance ROI. All math runs in your browser — nothing is sent anywhere.
$9.77M
estimated annual breach exposure
Based on industry average breach cost. Does not include regulatory fines.
$1.25M
estimated annual internal build cost
5 FTE senior engineers at industry salary benchmarks. Your cost may be lower or higher.
Professional
recommended Arbitex plan
Based on organization size and industry. Talk to us for exact pricing.
These estimates are conservative starting points based on published industry data and salary benchmarks. They are intended to frame the business case, not replace a detailed analysis. Talk to an Arbitex engineer for a calculation specific to your environment.
See what governance saves at your scale.
Enter your AI usage profile to estimate the cost of manual review, risk exposure from uninspected traffic, and compliance overhead — then see what Arbitex eliminates. All math runs in your browser.
$187K
annual savings vs manual review
Based on analyst time to manually review flagged requests at industry salary benchmarks.
90,000
sensitive requests caught per month
Requests containing PII, credentials, or regulated data that would pass uninspected without DLP.
520 hrs
annual compliance hours saved
tamper-proof audit logs and compliance evidence packs eliminate manual log assembly and examiner prep.
Estimates use conservative assumptions: $85/hr fully-loaded analyst cost, 3-minute average manual review time per flagged request, and 40 hours/month baseline compliance overhead. Your actual savings depend on your industry, team size, and regulatory requirements.
What does the point-solution stack cost?
Many enterprises assemble AI governance from multiple vendors — DLP, identity, audit logging, policy management. Use the slider to see how the stack total compares to a consolidated platform.
Point-solution estimates based on published list prices for enterprise DLP, CASB/SSE, and identity governance tools ($150K–$300K per vendor per year at mid-market contract sizes). Actual pricing varies.Talk to us for a specific comparison.
How long does an internal build actually take?
Internal AI governance builds consistently run 18–36 months before reaching production maturity. Arbitex deploys in days. The gap is measurable exposure — every week without governance is a week AI runs uninspected.
DLP pipeline design, provider API abstraction, policy engine scoping. Security review. No enforcement in production.
Pattern library, NER models, audit log schema, identity integration. First production traffic — limited coverage.
Compliance bundles, audit export formats, examiner readiness. Provider churn and maintenance begin consuming roadmap capacity.
Regulatory penalty ranges by framework.
AI governance failures in regulated industries carry measurable financial consequences. These are published penalty ranges — not hypotheticals. A single enforcement action in healthcare or financial services can exceed the cost of enterprise AI governance infrastructure by an order of magnitude.
45 CFR §160.404. Criminal penalties up to $250K + 10 years imprisonment for willful disclosure. AI-assisted PHI handling is a covered activity.
15 U.S.C. §6823. Covers financial institutions subject to the Safeguards Rule — including insurers offering financial products. NPI handling failures are in scope.
15 U.S.C. §7241–7244. IT control failures supporting financial reporting — including AI systems in scope for SOX §404 — are subject to SEC enforcement.
Penalty figures from published statutes and regulations. Actual penalties depend on violation severity, cooperation, prior history, and jurisdiction. This is not legal advice. Consult qualified legal counsel for your specific situation.
Governance infrastructure that pays for itself.
Arbitex delivers measurable ROI on three dimensions. Risk avoidance alone — governance infrastructure that holds up under regulatory examination — justifies the cost. Token optimization and build-vs-buy economics are additive benefits.
Build the business case for your procurement review.
Arbitex engineers can walk through the specific risk vectors, compliance controls, and cost governance mechanisms relevant to your environment. Bring your compliance team.