Defacta

Defacta checks AI-generated text against credible sources, filters out hallucinations, and flags bias, manipulation, and deception. It returns structured, machine-readable results you can wire into any workflow - via a REST API, an MCP server, or a browser extension.

Why Defacta#

Large language models produce fluent text that is sometimes confidently wrong. Before you ship an AI answer to a user - or act on it - you need to know which claims hold up. Defacta turns that check into a single call.

• Catch hallucinations. Identify claims in AI output that credible sources do not support.
• Verify facts. Validate factual accuracy against real evidence rather than model confidence.
• Flag manipulation. Surface bias, manipulation, and deception patterns in the text.
• Get structured output. Results come back as JSON you can parse, store, and act on programmatically.

Ways to use Defacta#

• REST API - call it from any backend or pipeline.
• MCP integration - plug verification directly into AI agents and tools that speak the Model Context Protocol.
• Browser extension - fact-check content in place, right where you read it.

This is a demo documentation preview generated from the Defacta website to show how the product could look on Docsbook. It is not the official Defacta documentation.