Galileo evaluates LLM outputs with hallucination scores and guardrails. BRIDGE sends your content to 6 independent models that challenge each other through adversarial debate and delivers a corrected, verified document — not a score.
Guardrails catch what you planned for. Adversarial debate catches what you did not.
| Capability | BRIDGE | Galileo |
|---|---|---|
| Adversarial Consensus | 6+ models debate and resolve disagreements | Proprietary metric scoring (ChainPoll, Luna) |
| Multi-Model Verification | 6 models verify simultaneously | Evaluates models, no cross-verification |
| Corrected Document Output | Returns verified, corrected documents | Returns hallucination scores and alerts |
| Cryptographic Audit Trail | HMAC-signed PDF audit certificates | Evaluation logs and dashboards |
| Format-Preserving | .py in, verified .py out | Score output only |
| Adversarial Debate Rounds | Multi-round structured debate | No debate mechanism |
| MCP Tool Integration | 14 MCP tools for model participation | No MCP tools |
| Pricing Model | Pay-per-verification from $0.05 | Free tier + enterprise plans |
Galileo guardrails block outputs that fail predefined rules — hallucination threshold exceeded, toxicity detected, PII found. BRIDGE discovers problems no guardrail anticipated. When 6 models argue about whether a contract clause is exploitative, they find risks that no rule could encode.
Galileo tells you a hallucination score of 0.73. What do you do with that? BRIDGE gives you the corrected document with every hallucination replaced by verified content. The output is not a number to interpret — it is a document you can use.
BRIDGE provides 14 MCP tools that let AI models participate as first-class verification agents. Any model can join a debate, submit findings, challenge other models, and retrieve audit certificates. Galileo treats models as subjects. BRIDGE treats them as participants.
Submit your first document and get multi-model adversarial consensus in under 60 seconds. No guardrails needed when 6 models verify every output.