Risk
Unpredictable outputs
GenAI models can hallucinate, misinterpret edge cases, or amplify bias — creating hard-to-price legal and operational risk for enterprises.
Safety Net for AI
RUSTY ELEMENT INC.
Pay-as-you-go
liability protection for Generative AI.
SaNAI aggregates multiple GenAI models, records every interaction on-chain, and connects claims to a DAO of experts. Deploy AI with the same confidence that insurance once unlocked for cars.
SaNAI는 여러 개의 생성형 AI를 한 번에 사용하고, 모든 질의·응답을 블록체인에 기록하며, 손해 발생 시 전문가 DAO가 보상 여부와 규모를 결정하는 AI 세이프티넷 플랫폼입니다.
Flexible per-transaction deductible.
Designed to evolve into full AI (re)insurance.
TAM
25M users · $23B services
Year 2 target
$0.5B annual revenue
Data flywheel
Q&A, feedback & RLHF streams
On-chain audit trail
Query: “Approve this loan portfolio?”
Model responses
Model A
Model B
Model C
Every answer is recorded immutably via blockchain & IPFS — so
root-cause analysis and recourse are finally possible.
Coverage snapshot
24h / 1M tokens
pooled mutual coverage
pooled mutual coverage
DAO validators verify loss, match it against the on-chain history,
and allocate compensation from the mutual fund.
Problem
AI is shipping faster than liability.
Generative AI is already in critical workflows — but no standard, neutral process exists to compare models, trace failures, or compensate parties harmed by wrong answers.
Liability
Accountability vacuum
When harm occurs there is no standard recourse: who pays — model provider, integrator, data owner, or end user?
Forensics
Root-cause obscurity
Tuning, prompts, plugins, sensor data and runtime all interact. Pinpointing what failed — and how to prevent it — is rarely possible today.
Market
No neutral benchmark
Model providers lack a shared environment to compare outputs on identical queries, slowing competitive pressure and safety improvements.
Solution
A safety-net layer under every AI interaction.
SaNAI combines multi-model access, immutable logging, and mutual-aid style coverage — bootstrapping an AI reinsurance layer as data and participation grow.
Core capabilities
Liability
Pay-as-you-go damage coverage per query.
Diversity
Aggregate responses from multiple GenAI models.
Immutable
Blockchain & IPFS audit trail for every interaction.
DAO claims
Experts assess eligibility & compensation.
Data value
Label-ready Q&A & feedback streams.
Insurance
Data foundation for AI (re)insurance products.
Users gain controlled access to multiple models, transparent context windows, and a clear path to recourse when things go wrong — all without locking into a single vendor.
Why now?
As AI moves from experimentation to regulated industries, safety, auditability, and financial backstops become prerequisites — not optional add-ons.
SaNAI is designed as an industry-wide utility rather than a single-model product: any model, any channel, one shared infrastructure for trust, audit and compensation.
- Supports multi-LLM orchestration from day one.
- Neutral DAO-based adjudication of claims.
- Aligned incentives via mutual fund + RLHF data revenue.
How it works
From query to compensation.
Two flows: everyday usage of multiple GenAI services with coverage, and a transparent compensation process when users submit a claim.
1. Using Multiple GenAI Services
1
User submits a professional query
The user sends a query through SaNAI — for example, legal, financial, or
operational questions where errors matter.
2
SaNAI routes to multiple models
Several GenAI engines respond in parallel. Their outputs are collected and
displayed for comparison.
3
Everything is logged on-chain
Queries, responses, and metadata are stored via blockchain & IPFS, creating an
immutable record for future audits and claims.
4
Expert refinement & feedback
DAO validators and expert panels can annotate outputs, improving individual
AIs and generating high-value RLHF data.
2. Compensation Claim Procedure
A
User requests compensation
A user experiences damage allegedly caused by an AI-guided decision and files a
claim via SaNAI.
B
Evidence & fact-check
The claimant uploads proof of loss. DAO validators match it against the
on-chain query/response trail and verify actual implementation details.
C
Expert evaluation
The DAO evaluates causality, negligence and impact, then proposes compensation
or penalties according to predefined policies.
D
Payout from mutual fund
Approved claims are paid out from pooled fees, with
decisions recorded openly for future precedent and training.
Market & Business
A $23B+ services market with no safety layer.
SaNAI mirrors how insurance unlocked the automotive era: turning unpriced risk into a sustainable industry by aligning operators, users, and underwriters.
TAM · SAM · SOM
25M / 8M / 1M
Target segments range from heavy GenAI subscribers to flexible pay-as-you-go users, representing up to $23B in annual service revenues.
Revenue streams
$512M+
Usage royalties, mutual fund income, anonymized Q&A & feedback data sales, and expert RLHF datasets together target $0.5B+ in Year 2 annual revenue.
Mutual fund
$10.8M
A dedicated mutual fund, capitalized from usage fees, backs compensation payouts and seeds a transition into full AI (re)insurance.
Growth strategy
From pilot platform to AI reinsurance.
SaNAI’s roadmap builds from MVP and early adopters to becoming the foundational safety layer for the AI industry.
Capital & execution focus
Seed funding is concentrated on:
- Concept and technical verification of the blockchain-based evaluation system.
- Design & build of the Pilot / MVP platform (UI/UX, front & back end).
- AI agent integration and DAO evaluation prototype.
- Marketing, partnerships and expert network onboarding.
Budget allocation: R&D 40%, Marketing & Networking 35%, Operations 20%, Contingency 5%.
Timeline
Phase 1–2 · Short term
Launch platform & data flywheel
Release MVP, onboard early adopters, and start building a critical mass of query–response data.
Phase 3 · Year 2
Partnerships & tokenization
Secure partnerships with major AI providers and enterprises. Develop proprietary stablecoin and utility token. Target $0.5B annual revenue and SOM penetration.
Phase 5 · Year 3
Automated compensation & SAM
Integrate AI agents to automate evaluation of minimum compensation standards and reach SAM coverage.
Phase 7 · Long term
AI insurance & reinsurance
Transition into full AI insurance and reinsurance services, becoming the foundational safety layer underpinning the AI economy.
Team
Experts at the intersection of AI, risk & finance.
RustyElement brings together leaders from AI research, insurance, blockchain, and regulatory policy to design a system the whole industry can trust.
C1
Founder & CEO
Chief Architect
15+ years in AI infrastructure and large-scale platforms; previously led deployment of safety-critical ML systems in finance.
C2
Risk & Insurance
Chief Risk Officer
Veteran in reinsurance & actuarial science, designing products that convert emerging technologies into bankable asset classes.
C3
Blockchain & DAO
Head of Protocol
Built and operated large-scale blockchain networks; deep experience with token economics and decentralized governance.
C4
Policy & Governance
Head of Regulatory
Former regulator and policy advisor, shaping AI and data-protection frameworks across multiple jurisdictions.
Ready to build an AI safety net for your stack?
Share your use cases and risk profile, and we’ll walk you through SaNAI’s pilot
program, technical architecture, and partnership options.
Or email us at hello@rustyelement.ai