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. SaNAI는 여러 개의 생성형 AI를 한 번에 사용하고, 모든 질의·응답을 블록체인에 기록하며, 손해 발생 시 전문가 DAO가 보상을 결정하는 AI 세이프티넷 플랫폼입니다.
TAM
$23B
Target Rev
$0.5B
Coverage
DAO-Verified
On-chain Audit
Block #19284...
Query
"Approve this loan portfolio?"
Model A
Risk: High
Model B
Risk: Med
Immutable Record: Responses hashed & stored via IPFS.
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.
Accountability vacuum
When harm occurs there is no standard recourse: who pays — model provider, integrator, data owner, or end user?
Root-cause obscurity
Tuning, prompts, plugins, sensor data and runtime all interact. Pinpointing what failed — and how to prevent it — is rarely possible today.
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.
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.
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.
C
Expert evaluation
The DAO evaluates causality, negligence and impact, then proposes compensation or penalties.
D
Payout from mutual fund
Approved claims are paid out from pooled fees, with decisions recorded openly for future precedent.
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.
Ready to build an AI safety net?
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 info@rustyelement.com