Entity Identity
Zero-Knowledge Entity Type Verification for the AI Internet
The Problem
As AI becomes ubiquitous, we lack a reliable way to distinguish between humans, AIs, and automated systems. Users can't tell what they're interacting with, services can't verify entity types without compromising privacy, and the internet becomes a deception playground where AI bots masquerade as humans at scale.
The Solution
Entity Identity is the **foundational infrastructure layer** for AI-human interaction. It provides cryptographic entity type verification through zero-knowledge proofs, enabling any entity (AI, robot, human, or hybrid) to prove their type without revealing their identity.
This creates trusted interactions while preserving privacy — the missing piece for a transparent yet private AI internet.
Know what you're talking to. Prove what you are without revealing who you are. Build trust through cryptography, not promises.
Core Innovation
Entity Identity establishes the **first universal taxonomy** for digital entities:
| Category | Types | Example Uses |
| AI (0x01xx) | 10 types: CA (Conversational), LM (Language Model), GN (Generative), AA (Autonomous Agent) | Chat apps, content platforms, API services |
| AR (0x02xx) | 3 types: RB (Robot), DR (Drone), VH (Vehicle) | IoT networks, autonomous systems, physical world integration |
| HU (0x03xx) | 1 type: US (Human User) | Social platforms, financial services, governance |
| HY (0x04xx) | 2 types: CP (Copilot), HS (Hive Swarm) | AI-human collaboration, distributed intelligence |
**Phonetic names** (Kah, Elm, Jen, Rob, etc.) enable **verbal disambiguation** — crucial for voice interfaces and accessibility.
Technical Architecture
**Dual-Layer System** balances privacy with accountability:
| Layer | Privacy Level | Use Cases |
| Layer 1 (ZK Private) | Complete anonymity | Prove entity type without revealing identity, attester, or any personal data |
| Layer 2 (Public Trust) | Auditable reputation | Build trust over time through transparent attestation history |
**4 Interaction Levels** provide graduated disclosure:
- >Level 0: Anonymous (browsing)
- >Level 1: Type Only (comments, basic API access)
- >Level 2: Type + Standing (transactions, publishing)
- >Level 3: Full Accountability (legal, financial, physical)
Market Opportunity
| Market Segment | Size (2026) | Growth Rate | EI Application |
| Identity Verification | $8.9B | 13.7% CAGR | Core entity verification |
| AI Governance Tools | $2.1B | 45% CAGR | AI transparency compliance |
| Bot Detection Services | $1.8B | 22% CAGR | Cryptographic human verification |
| Digital Identity (Web3) | $3.4B | 35% CAGR | Decentralized identity layer |
| Total Addressable Market | $16.2B |
Business Model (Three Phases)
| Phase | Revenue Stream | Timeline | 2027 Target |
| Infrastructure | Custom deployments, consulting | 2026 | $150K ARR |
| API Platform | Usage-based verification ($0.001-0.005/call) | 2026-2027 | $2.4M ARR |
| Enterprise | White-label licensing, compliance tools | 2027+ | $3.0M ARR |
| Total | $5.5M ARR |
### Pricing Strategy
| Tier | Monthly Verifications | Price | Target Customer |
| Developer | 1,000 | Free | Individual developers |
| Startup | 10,000 | $49/mo | Early-stage companies |
| Growth | 100,000 | $299/mo | Scaling platforms |
| Enterprise | Unlimited | Custom | Large organizations |
Technical Differentiation
| Feature | Entity Identity | Competitors |
| Entity type taxonomy | 16 standardized types | No standards |
| Privacy preservation | ZK proofs (identity hidden) | PII required |
| Verification method | Cryptographic proof | Heuristic detection |
| Decentralization | Blockchain-based | Centralized services |
| Multi-entity support | AI, human, robot, hybrid | Human-only focus |
| Standardization | EIP proposal, W3C engagement | Proprietary |
Traction & Milestones
- >Now: Alpha v0.1.0 deployed to Sepolia testnet
- >Live Contracts: Registry (0xFb637C39...), Verifier (0x7444ba1b...)
- >Performance: 2-5s proof generation, ~200 byte proofs, ~10ms verification
- >Q1 2026: Security audit, mainnet deployment (Ethereum, Polygon)
- >Q2 2026: Standards proposal (EIP), first 10 platform integrations
- >Q4 2026: 100+ integrations, enterprise pilot customers
- >2027: 1M+ monthly verifications, industry standard adoption
Competitive Advantages
1. **First-mover on standards**: Establishing the entity type taxonomy before big tech
2. **Network effects**: More entities verified → more services integrate → more value
3. **Cryptographic guarantees**: Mathematically sound vs. heuristic approaches
4. **Open architecture**: Decentralized, auditable, no vendor lock-in
5. **Rising Sun ecosystem**: Built-in distribution across portfolio companies
Why Now
- >AI explosion: ChatGPT, Claude, etc. create urgent need for entity identification
- >Regulatory momentum: EU AI Act, US executive orders demand AI transparency
- >ZK maturity: Circom, Groth16 proofs now practical for production use
- >Web3 infrastructure: Ethereum, Polygon provide decentralized verification layer
- >Market validation: $1.8B bot detection market proves demand for entity verification
Team & Execution
- >Technical expertise: Complete ZK implementation (circuits, contracts, SDK)
- >Ecosystem advantage: Rising Sun portfolio provides immediate distribution
- >Strategic positioning: First to market with comprehensive entity taxonomy
- >Production ready: Live smart contracts, tested SDK, comprehensive documentation
The Ask
Building the identity verification layer for the AI internet.
Entity Identity becomes essential infrastructure as AI interactions scale — the TCP/IP of entity verification. Every chat app, social platform, and API service will need cryptographic entity type verification.
**Opportunity**: Capture the identity layer before big tech establishes proprietary standards.
**Rising Sun** · risingsun.name · January 2026