NewOpen Source
OpenSEO
★ 6.2kOpen-source SEO platform for humans and AI agents
Active repoRelease v0.1.1
ToolNew
LLMrefs
Track rankings and citations inside generative search
PricingPaid
CategoryAI Visibility
Data checkedtoday
Listing status● Verified
Overview
What is LLMrefs?
LLMrefs monitors how brands and pages appear for selected questions across AI answer engines, surfacing rankings, citations, competitors and changes over time. Its documented capabilities include LLM rank tracking, Citation discovery and Competitor monitoring.
LLMrefs sits in the measurement layer of a modern search stack. Its role is to turn otherwise inconsistent AI answers into signals a team can monitor, compare and use when prioritizing visibility work.
Best forBrand, SEO and growth teams measuring how they appear in AI-generated answers.
Primary workflowAI visibility measurement
Delivery modelHosted SEO software or managed web application
Pricing modelPaid
Product preview
Capabilities
What it helps you do
01
LLM rank tracking
Use llm rank tracking to establish a repeatable baseline and surface changes that deserve investigation instead of relying on occasional manual checks.
02
Citation discovery
Use citation discovery during discovery, when the team gathers evidence before deciding which opportunities, queries or competitors deserve deeper work.
03
Competitor monitoring
Use competitor monitoring to establish a repeatable baseline and surface changes that deserve investigation instead of relying on occasional manual checks.
04
Historical visibility trends
Use historical visibility trends to understand how the brand or site is represented across search and answer surfaces, not only whether a traditional result received a click.
Workflow
How LLMrefs fits into the work
01
LLM rank tracking
Use llm rank tracking to establish a repeatable baseline and surface changes that deserve investigation instead of relying on occasional manual checks.
02
Citation discovery
Use citation discovery during discovery, when the team gathers evidence before deciding which opportunities, queries or competitors deserve deeper work.
03
Competitor monitoring
Use competitor monitoring to establish a repeatable baseline and surface changes that deserve investigation instead of relying on occasional manual checks.
Decision guide
What to know before choosing
A good fit when
- ✓You need support for AI Visibility and GEO in a defined workflow.
- ✓The workflow is important enough to justify evaluating a paid product and its current plan limits.
- ✓Your stack already includes or can work with ChatGPT, Perplexity, Gemini, Claude.
Verify before adopting
- →Confirm which capabilities are included in the current paid offering and whether usage limits apply.
- →Check integrations, export options and how the product fits your existing reporting or publishing process.
- →Validate the depth and scale of historical visibility trends for your team.
Categories
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