No product description has been published for this domain yet. Everything below is measured directly.
Research & Analysisgltr.ioTracked since 2026-08-192 discovery sources
8.1KBacklinks
886Referring domains
24Domain authority
-4.3%Referring domains · 90 days
Authority & distribution
How strong is GLTR’s web footprint?
Backlinks measure accumulated distribution; referring domains show how broadly that authority is spread. Both are observable on the open web, so both are published for every product here.
Backlinks
8.1KCurrent snapshot
Referring domains
886Current snapshot
Authority
24Domain authority · category median 21
90-day move
-4.3%Referring domains, last 90 days
At 24, GLTR sits above the 21 median for its category.
Trajectory · Pro
The counts above are the latest of 370 daily observations. The curve through them is on the full profile.
Traffic makes more sense when you can connect it to the actual product promise.
“GLTR”
No usable description reached this profile from any discovery source, so none is shown. The measured signals below are unaffected.
Research & AnalysisSeen 2026-08-19 → 2026-08-21Coverage tier C
What we have measured
4 of 8 signal groups are available for this product: identity, authority and backlinks, AI referrals, search demand.
Not measured for this domain: traffic and engagement, audience demographics, country distribution, acquisition mix. Those sections are left out of the page rather than filled with estimates.
Canonical website: http://gltr.io/
Observed across 2 discovery sources.
Research questions
What the evidence answers about GLTR.
Every answer is tied to a source we collected, and the questions with no evidence behind them are left unanswered rather than guessed.
Who is the primary audience for GLTR?
The primary audience for GLTR includes researchers and individuals concerned with content authenticity and the forensic analysis of text. The tool was developed as a collaboration between the MIT-IBM Watson AI lab and HarvardNLP, indicating its utility for academic and technical scrutiny.
What features, tools, or integrations does GLTR offer?
GLTR offers a live demo for users to try the tool directly. It provides source code on Github for inspection and modification. The core feature is a visual forensic tool that analyzes the predictability of words in a text to detect AI generation.
What is GLTR and what problem does it solve?
GLTR is a forensic tool that detects automatically generated text. It enables users to inspect the visual footprint of text to determine if it was likely produced by a large language model, helping to identify potential fake reviews, comments, or news articles. The tool provides a visual forensic analysis to see if text is too predictable to be from a human writer.
What is GLTR used for, and in what situations?
GLTR is used to perform forensic analysis on text to determine the likelihood it was automatically generated. It is applicable in situations where verifying the authenticity and human origin of content is critical, such as investigating potential online misinformation or fake reviews. The tool allows users to check a live demo to analyze text samples.
4 of 6 research questions are answered for this product. The rest need source evidence we have not collected yet, so they are left unanswered rather than guessed.
Behind the lock
Unlock full GLTR intelligence.
Backlink trajectoryThe figures above are the latest observation. The daily curve behind them holds 370.
AI referral detailHow much traffic assistants send, which one of them does it, and the page they land on.
Search structure and ranking depthOrganic against paid, brand against non-brand, and how many keywords rank in the top three against the long tail — which is what decides whether the demand is portable or tied to the name.
The rest of the marketPage through every leaderboard 100 rows at a time, put any five products side by side, and query the whole dataset over API / MCP.
Worldwide estimates · Data period 2026-05-01 → 2026-07-31. Figures are measured estimates intended for market research. Signals we have not measured for this domain are omitted, never estimated; a measured zero is still reported as zero. How this was measured