Gable is a data change management platform that provides full data visibility and governance by scanning application code to detect data-producing code.
Data & Analyticsgable.aiTracked since 2026-08-211 discovery source
1.6KBacklinks
504Referring domains
22Domain authority
+18.4%Referring domains · 90 days
Authority & distribution
How strong is Gable’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
1.6KCurrent snapshot
Referring domains
504Current snapshot
Authority
22Domain authority · category median 22
90-day move
+18.4%Referring domains, last 90 days
At 22, Gable sits above the 22 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.
“Gable”
Gable is a data change management platform that provides full data visibility and governance by scanning application code to detect data-producing code.
Data & AnalyticsSeen 2026-08-21 → 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: https://www.gable.ai
Observed across 1 discovery source.
Research questions
What the evidence answers about Gable.
Every answer is tied to a source we collected, and the questions with no evidence behind them are left unanswered rather than guessed.
What is the core function of Gable and what problem does it solve?
Gable is a data change management platform that provides full data visibility and governance. It solves the problem of answering where sensitive data flows by using static analysis of source code to trace data flows from consumer apps through backend systems. It allows teams to answer audit and compliance questions with confidence, as stated on its homepage.
In what situations is Gable typically used?
Gable is used for compliance, privacy, and model risk reviews where teams need to understand data lineage. It is specifically used when auditors ask where data comes from and where it goes, providing answers in minutes through static code analysis. This is highlighted in its main homepage text.
Who is the primary audience for the Gable platform?
The platform is for teams that need to answer audit and compliance questions about data flow with confidence. Its homepage explicitly states it helps teams do this. The product is categorized under Data & Analytics, suggesting it's for data-centric roles.
What key features or methods does Gable offer for data lineage?
Gable offers code-level data flow lineage through static analysis of source code. It traces data from source to destination without runtime agents, sampling, or production overhead, as shown in its main text and code example. This is its core method for providing data visibility.
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 Gable intelligence.
Backlink trajectoryThe figures above are the latest observation. The daily curve behind them holds 370.
AI referral detailHow much traffic assistants send.
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