Problem solved

Abliteration.ai solves the problem of LLM refusal behavior blocking legitimate professional work in security, trust and safety, and ML research. It provides an OpenAI-compatible unrestricted API with enterprise policy controls, audit logging, per-project keys, and zero retention by default, enabling teams to build applications and generate data that other providers refuse to handle.

Use cases

• AI red teaming and adversarial testing
• Cybersecurity vulnerability research and exploit explanation
• Trust and safety policy testing and training data generation
• Synthetic dataset creation for model training and evaluation
• ML research requiring unfiltered model responses
• Defense and government contractor workflows

Audience

• Developers
• ML Engineers
• Data Scientists
• Enterprise
• Researchers

Pros

• OpenAI-compatible and Anthropic-compatible APIs require minimal code changes
• Enterprise policy gateway with policy-as-code and per-project keys
• Zero data retention by default
• Supports batch synthetic data generation with schema validation
• Designed for high-risk professional workflows like red teaming and trust and safety

Cons

• Potential for misuse if not governed properly
• Pricing details not publicly transparent
• Requires enterprise policy configuration to ensure compliance
• Limited information on underlying model training and safety benchmarks
• Not suitable for general consumer applications needing standard content moderation