How do AI engines resolve Kenyan name collisions
AI answers reveal which sources speak for Kenyan businesses.
Kijito Citation Lab studies how answer engines cite, borrow and sometimes misplace authority when they describe Kenyan businesses. A Nairobi shop, a county supplier, a coastal tour operator or a social-first merchant may be represented through its own page, a registry trace, a map listing, a local article, or an overseas platform profile. The lab follows those paths in English and Swahili, then asks whether the cited evidence really supports the visible claim.
Method in brief
How the lab follows citations
A recorded observation is more than a model answer. The lab keeps the prompt wording, language variant, cited source and visible claim together, so the path can be reviewed later. Samples are built around business categories, counties, language choices and evidence types.
Repeatability matters because one answer is thin evidence; comparable runs show whether a pattern holds, shifts or collapses under a slightly different phrasing.
In focus now
…Kenyan-owned pages, official local records and county references competing with maps, social profiles and international aggregators…
The lab is studying how Kenyan-owned sources, official local records, county references, trade-body mentions, maps, social profiles and international aggregators compete inside AI answers. Special attention goes to cases where English and Swahili queries point to different source paths for the same business.
Research notes in progress
The research index gathers source-path reviews, bilingual query comparisons, citation-support checks and entity-collision notes about Kenyan businesses.
Can SMEs track citation share over time
Does Nairobi get richer AI citations
See which evidence is allowed to speak for a Kenyan business.
The lab tracks the citation trail behind AI answers, then marks what is supported, weak, mixed or unresolved.
Contact the lab →