AI Baseline Test
Record how AI initially understands, cites, and recommends a new brand.
Establish baseline
LingNav AILINGNAV EXPERIMENT · REAL-WORLD TEST
Can a new brand
become visible to AI?
We do not use fabricated customer stories. LingNav is testing the GEO method on its own brand and documenting whether AI understanding changes.
R&DREAL EXPERIMENTSELF-VALIDATED
EXPERIMENT DESIGN
Same brand. Same questions. Repeated tests.
Control the variables, document the process, and let observable evidence—not marketing claims—shape the conclusion.
Website Foundation
Create a clear and machine-readable foundation for the brand and its offer.
Build foundationInformation Optimization
Strengthen entity relationships, content structure, and credible evidence.
Implement changesAI Recheck
Repeat the same questions and track changes in AI understanding.
Verify change01
Transparent
State the subject, method, steps, and limitations.
02
Repeatable
Keep the prompt set and test logic consistent.
03
Evidence-led
Use observable change—not invented metrics—as the result.
DAY 0 · REVIEWED BASELINE
A first-party Kimi baseline, not a customer case
LingNav completed its own Day 0 baseline with 8 prompt categories and 2 runs per category. It is a directional first-party experiment, not independent validation or a cross-platform score.
LingNav was not organically surfaced in the reviewed unaided Kimi prompt set. When its name was supplied, the model could repeat or process that identity, but this was not treated as independent discovery or recommendation.
Current status: Day 0 baseline and evidence inventory complete; first public optimization in progress; no re-test has been run yet.
READY TO START
Ready to discover
your AI visibility?
See how AI systems understand, cite, and recommend your business.
Start AI Visibility Audit ↗