venice-private-ai

name	venice-private-ai
description	Use Venice AI for private, no-data-retention LLM inference. OpenAI-compatible API with privacy guarantees — no prompts, completions, or user data stored. Use when asked about private AI inference, confidential reasoning, Venice API, or zero-retention LLM providers.

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:

1. ClawWall DLP — prevents sensitive data (private keys, mnemonics) from reaching any LLM
2. Venice inference — zero-retention processing of financial data
3. Domain constraint — agent cannot access email, files, browser — only blockchain
4. 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