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Defacta

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Defacta sits between AI-generated or external text and the moment that text gets used in a decision, filing, article, or publication. It runs each piece of content through a structured, multi-stage verification pipeline that checks claims against independent sources, fact-checking registries, and credibility signals. The system flags hallucinations, fabricated citations, unsupported assertions, bias, manipulation patterns, and misleading framing, then produces a full-spectrum report combining findings, source metadata, risks, and recommended actions. Three independent LLMs run in parallel during analysis, and disagreement between models is treated as its own signal. Every report is timestamped and SHA-256 hashed, creating a durable audit trail with job history, integrity checks, and evidence records. Users can edit flagged text, generate repair prompts, re-check changes, and compare versions within revision workflows, then export results to PDF, DOCX, Markdown, JSON, XLSX, or TXT. Defacta connects through an API, an MCP server, and a browser extension, fitting into existing workflows for both individual verification and agent-to-agent pipelines inside enterprise systems. It serves analysts, compliance teams, journalists, researchers, and enterprise AI teams across legal, finance, media, consulting, and GRC functions.

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