Enterprise AI
A major retail brand
A retail brand's campaigns now convert 25% better
- Retail
- Client under NDA
- Global
- 25%
- Higher conversion, with more repeat purchases
Broad campaigns were losing precision, and engagement and loyalty were slipping.
What we did
We set a baseline from customer behavior and demographics, then built preference models that feed a personalization engine. A pilot ran first. Then it went to every channel, and the models are refined as results come in.
Related work
See all- A major financial institution
Financial Services/Client under NDA
A major financial institution saw 25% fewer fraudulent transactions after we put machine-learning scoring inside its banking systems.
25%
Fewer fraudulent transactions, caught in real time
- A manufacturing group
Manufacturing/Client under NDA
A manufacturing group lowered supply chain costs 20% with demand and inventory forecasts that feed its ERP.
20%
Off supply chain costs, with shorter lead times
- A metropolitan transit network
Government & Public Sector/Client under NDA
A metropolitan transit network's voice line now resolves 70% of calls without a person, in eleven languages.
70%
Calls resolved without a person
Tell us which system the AI has to run inside
If that system is not ready for AI yet, tell us that too. An engineer will reply and say plainly whether we are the right firm for it.