Ever pasted an AI answer into a document, hit send, and then wondered - is any of this actually true?
AI outputs look authoritative. But they routinely hallucinate facts, fabricate citations, and frame things in misleading ways. For anyone working in legal, finance, compliance, publishing, or research, that's a real problem.
At Defacta, we build an independent verification layer between AI-generated or external text and its use in decisions, publications, filings, articles, social media posts, or other contexts.
We don't offload everything to AI. Instead, we replicate the human verification process as a structured, multi-stage pipeline. LLMs are used only to accelerate specific steps, always constrained by fresh data retrieval and source-grounded analysis. Human expertise is essential to meaningful verification, and we value journalists, fact-checkers, and analysts whose contributions should be recognized and fairly compensated.
The system checks text against credible sources, databases, and fact-checking registries, checking claims and identifying hallucinations, fabricated citations, misinformation, and manipulative framing.
All findings are traceable and source-backed. Human input and oversight remain central.
Defacta serves analysts, compliance teams, journalists, and others working in high-risk environments where accuracy is critical, or any curious-minded person. We cover both personal verification and agent-to-agent workflows inside enterprise pipelines, connecting them through a single audit trail.
Documents can enter at any stage. A user or a team receive structured reports with findings, sources, and recommended actions. Existing workflows remain unchanged, with optional API integration.
Defacta does not replace legal or editorial responsibility. It does not edit documents; it flags and highlights issues and provides a clear audit trail of verification.