jiayaoqijia Venice Private AI
Private LLM inference via Venice AI — an OpenAI-compatible API with zero data retention.
Why Venice for Agents
Venice provides "private cognition" — the LLM processes sensitive data (portfolio values, trading strategies, wallet addresses) without retaining any of it. This is critical for agents handling:
- Confidential treasury management
- Private governance analysis
- Sensitive due diligence on DeFi positions
- Deal negotiation without data leakage
API (OpenAI-compatible)
Base: https://api.venice.ai/api/v1
Uses standard OpenAI API format. Requires
Authorization: Bearer YOUR_VENICE_API_KEY.
Chat completion (private, zero retention):
exec command="curl -s -X POST 'https://api.venice.ai/api/v1/chat/completions' -H 'Content-Type: application/json' -H 'Authorization: Bearer YOUR_KEY' -d '{\"model\":\"venice-uncensored\",\"messages\":[{\"role\":\"user\",\"content\":\"Analyze this DeFi position...\"}]}'"
List models:
web_fetch url="https://api.venice.ai/api/v1/models" headers="Authorization: Bearer YOUR_KEY"
Available Models
| Model | Type | Use Case |
|---|---|---|
venice-uncensored |
Text | General reasoning, uncensored |
llama-3.3-70b |
Text | Strong general purpose |
qwen-2.5-coder |
Code | Code generation |
deepseek-r1-671b |
Text | Deep reasoning |
Ottie Integration
Venice works as a drop-in provider via Ottie's OpenAI-compatible provider. Config:
{
"model_list": [{
"model_name": "venice-private",
"model": "venice/venice-uncensored",
"api_base": "https://api.venice.ai/api/v1",
"api_key": "YOUR_VENICE_KEY"
}]
}
Privacy Guarantees
- Zero data retention: no prompts, completions, or metadata stored
- No training on user data: queries never used for model training
- No logging: inference requests are not logged
- Decentralized: inference runs on distributed GPU infrastructure
Privacy Architecture for Agents
Combine Venice with Ottie's security model:
- ClawWall DLP — prevents sensitive data (private keys, mnemonics) from reaching any LLM
- Venice inference — zero-retention processing of financial data
- Domain constraint — agent cannot access email, files, browser — only blockchain
- On-chain verification — all actions produce verifiable on-chain receipts
Use Cases
- Private treasury copilot: analyze portfolio without exposing holdings to LLM provider
- Confidential governance: evaluate DAO proposals using private voting preferences
- Risk assessment: process position data without metadata leakage
- Multi-agent coordination: agents share sensitive analysis via private inference channels