Defacta

Defacta is an independent verification layer that sits between AI-generated or external text and its use in decisions, publications, filings, articles, and other high-stakes contexts. It verifies content against credible sources, databases, and fact-checking registries, identifying hallucinations, fabricated citations, unsupported claims, misinformation, and manipulative framing.

Rather than offloading the entire process to AI, Defacta replicates the human verification workflow as a structured, multi-stage pipeline. Large language models are used only to accelerate specific steps, always constrained by fresh data retrieval and source-grounded analysis. Three independent LLMs run in parallel, and disagreement between models is treated as a verification signal in itself.

Users can submit pasted text, articles, URLs, or AI outputs and receive structured, evidence-backed verification reports. The system extracts key claims from submitted content and checks each one against independent sources and source credibility signals. Reports combine factual findings, source metadata, risk indicators, limitations, and human-review context into a single document.

Defacta performs full-spectrum analysis that goes beyond simple AI detection or plagiarism checking. It combines factual claim verification against trusted databases, source credibility assessment, and linguistic and framing analysis covering manipulation, loaded language, false equivalence, and selective omission. Proprietary logic algorithms catch internal contradictions and unsupported assertions within the text itself.

The platform detects bias, deception markers, and manipulation patterns regardless of the source or its stated agenda. Every finding is traceable and source-backed, with human input and oversight remaining central to the process.

Defacta produces a durable audit trail for every verification job. This includes job history, source metadata, SHA-256 hashes, integrity checks, and evidence records. Reports are timestamped and can be stored in private libraries, shared publicly, or exported to PDF, DOCX, Markdown, JSON, XLSX, and TXT formats.

The platform supports revision workflows that allow users to edit text, generate repair prompts or corrected drafts, re-check changes, and compare versions side by side. This makes it practical for teams that need to iteratively improve content accuracy before publication or submission.

Integration options include an API, an MCP server, and a browser extension, allowing Defacta to connect with existing workflows without requiring changes to current processes. It supports both personal verification use cases and agent-to-agent workflows inside enterprise pipelines, connecting them through a single audit trail.

Defacta serves analysts, compliance teams, journalists, consultants, and others working in high-risk environments where accuracy is critical. Target verticals include legal, finance, media and publishing, research, enterprise AI teams, consulting, GRC, and content creation. It is also available to any curious-minded individual who wants to verify information before acting on it.

The platform is available on the web in English. It offers both a free version and a free trial. 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 for accountability and compliance purposes.