Venice Private AI
SkillCommerce & financeUse 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.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Venice Private AI skill
What this skill tells your AI
The instructions your AI receives, as published by jiayaoqijia/cryptoskill in skills/ai-crypto/venice-private-ai/SKILL.md and read by ahel’s review.
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
Signals
- GitHub stars
- 76
- Forks
- 16
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
venice-private-ai- Source
- github.com/jiayaoqijia/cryptoskill