Case Study · Media Monitoring Africa · Media

A media intelligence base of 2.5 millionarticles, with humans still in the loop.

Three AI platforms for one of Africa's most important media watchdogs: Dexter, i3 Africa and WITI.

Custom platformML / NLPMLOpsCivic tech
01

The situation

Monitoring Southern African media at scale means volume no human team can read, in languages and nuance no off-the-shelf model handles well.

MMA needed AI that amplifies its monitors' judgment instead of replacing it.

02

What we built

Dexter: a media intelligence platform scaled past 2.5 million articles — article ingestion, NLP analysis, tagging, monitoring and reporting in one workflow, extracting people, places, companies and quoted sources.

i3 Africa (Insights into Incitement): an AI classifier that triages potential incitement on a red-amber-green risk scale.

WITI (Who Influences The Influencer): a proof-of-concept turning TikTok and social video into transcribed, searchable, AI-analysed political-influence intelligence.

03

What changed

Early triage improved and the manual review burden dropped, while human monitors kept the final call on Southern African language and nuance.

A single 2.5m+ article intelligence base now underpins faster research workflows, more structured analysis and stronger reporting — work that used to require manual trawling.

AI that amplifies the watchdog, not one that replaces it.