Claim extraction
Separate core claims from surrounding narrative to make fact-checking more direct.
Explainable credibility analysis
TruthLens helps you inspect headlines, posts, and articles for weak sourcing, emotional manipulation, framing bias, and missing context, so you can understand what to trust, question, or verify next.
Built for careful readers who need signal clarity before sharing, citing, or publishing.
Product demo preview
"Breaking: officials are hiding plans for citywide power outages next Friday. Move your money and stockpile supplies now."
Credibility summary
Mixed / use caution due to missing primary evidence.
Risk flags
Urgency language, unnamed insiders, and broad institutional claims.
Source quality
No primary documents, no named experts, no publication chain.
Missing context
Timeline ambiguity and no baseline statistics for comparison.
Trusted framing for
StudentsJournalistsResearchersEducatorsEveryday readersFeature overview
Instead of one opaque score, TruthLens organizes output into a readable structure that shows why each caution was raised.
Separate core claims from surrounding narrative to make fact-checking more direct.
Identify persuasive framing, loaded language, and rhetorical pressure cues.
Surface missing attribution, weak sourcing patterns, and indirect evidence chains.
Highlight urgency tactics and emotionally charged wording designed to bypass scrutiny.
Call out missing baselines, omitted timelines, and absent comparative context.
Each caution comes with rationale so users can review and challenge the reasoning.
How it works
Step 1
Drop in a headline, article excerpt, post, or thread exactly as you encountered it.
Step 2
TruthLens evaluates claims, sourcing, framing, and context using a transparent rubric.
Step 3
Get a structured readout of what looks reliable, what is weak, and what to verify next.
Ready to evaluate content with more clarity?
No sign-in required. Start with your own content or open curated examples to see how TruthLens explains each signal.