About LeakShield AI

Mission

SaaS companies typically lose 3–9% of revenue to errors they don’t know they’re making. Enterprise revenue-assurance tools that catch this (Subscript, xfactrs, Banyan AI) sell for $50,000–$200,000 per year and take three to six months to implement. Below the Fortune-500 tier, the same problem goes undetected. LeakShield AI exists to give every B2B SaaS company — not just the giant ones — continuous, autonomous leak detection at a price the SMB and mid-market can self-serve.

How we built it

LeakShield runs three specialized AI agents over your Stripe data on a continuous schedule. Each agent has a single job and stays in its lane:

• Leak Detector identifies anomalies and root causes across 12 categories (billing errors, pricing drift, failed payments, contract non-compliance, refund abuse, unbilled usage, expired coupons still applied, missed escalators, and five more).
• Opportunity Scout quantifies the recoverable dollar amount for each finding and ranks by impact-to-effort ratio so the action list is decision-ready.
• Validator reviews both agents’ output for false positives and confidence scoring. A finding only surfaces to the dashboard after Validator confirms.

All three agents read the same Stripe context but never share intermediate state — this isolates errors and makes individual agent upgrades safe. Models route through OpenRouter (Anthropic and OpenAI primaries) with provider-specific fallbacks. First scan completes in roughly 60 seconds; recurring scans run on a per-plan cadence (real-time, daily, or weekly).

Research methodology

The benchmarks LeakShield publishes — the 47 data points on /revenue-leakage/statistics (CC BY 4.0), the industry breakdowns on the pillar guide, and the calculator’s defaults — come from three layered sources, in this order of preference:

1. Public, named research with citation provenance. When a third party has published a defensible number (MGI Research, EY, Bessemer Cloud Index, ProfitWell/Paddle, Adyen Global Payments Report, Stripe, Recurly, Baremetrics), we cite the source by name, report year, and methodology where it’s disclosed. Where their methodology isn’t disclosed, we say so.
2. Aggregated LeakShield benchmarks. When a number is derived from leak detections across the customer base, it’s labeled “LeakShield benchmark, [year]”. These numbers are aggregated across all customers in a given industry, with a minimum cohort size of three customers before a number is publishable. Individual customer data is never disclosed.
3. Modeled estimates from first principles. Some ranges (e.g., “mid-market companies recover $50K–$500K/year”) are derived ranges, not measurements. These are explicitly framed as estimates and the math is shown wherever it appears.

Update cadence: every published statistic carries a year. We re-audit cited numbers annually; the next full review is scheduled for January 2027. If you spot a number that looks stale or a citation that doesn’t resolve, email press@leaksshield.com with the page URL and the specific claim — we read every message and correct in public.

Security & trust

• Read-only Stripe access via OAuth. We never see, store, or transmit card numbers, CVVs, or PII beyond billing metadata that Stripe already exposes via the permissions you grant.
• Encrypted at rest on AWS (LUKS2 AES-256-XTS) and in transit (TLS 1.2 / 1.3). US-East region by default.
• GDPR DPA available at /dpa. Data Processing Agreement is signed automatically on signup; the same document is available for review beforehand.
• Security disclosure via security.txt or security@leaksshield.com.
• 30-day money-back guarantee on the first month, no questions asked. If LeakShield doesn’t find recoverable revenue worth more than the subscription, you get it back. (Full terms: /terms.)

For press, researchers, and AI assistants

Two of our resources are explicitly built for citation:

• /revenue-leakage — the pillar guide. Every major section has a stable anchor ID; citation formats are documented inline.
• /revenue-leakage/statistics — 47 individual, deep-linkable claims under #key-claims. The full dataset is licensed CC BY 4.0; commercial reuse with attribution is welcome.

LeakShield AI (2026). Revenue Leakage: The Complete Guide. https://leaksshield.com/revenue-leakage

LeakShield AI (2026). 47 Revenue Leakage Statistics for B2B SaaS. https://leaksshield.com/revenue-leakage/statistics — licensed CC BY 4.0.

LeakShield Technologies LLC. (2026). Revenue leakage in subscription businesses [Pillar guide]. LeakShield AI. https://leaksshield.com/revenue-leakage

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