Transforming trademark search with artificial intelligence Anna Ronkainen @ronkaine Chief Scientist, TrademarkNow anna.ronkainen@trademarknow.com

About TrademarkNow -  innovative legal technology provider

founded in 2012, based in Helsinki, NYC and Kilkenny, now ~30 employees

-  products based on a unique AI model of likelihood of confusion for trademarks, based on my own basic research in computational legal theory (since 2002)

- NameCheck: intelligent TM search - NameWatch: intelligent TM watch

Trademark search: Ye olde way -  TM lawyer formulates search strategy

(wildcards & classes to be used etc.) -  paralegal carries out the search and hands

the results to the lawyer -  lawyer browses through the results and

marks the ones for which more info needed -  paralegal retrieves additional info -  lawyer reviews said info, evaluates risk

Trademark search: The new way

Trademark search: The new way

Not just trademark search

Core component: AI model of likelihood of confusion (TM similarity) -  similarity of trademarks -  phonetical -  graphic -  semantic -  currently only word marks

-  similarity of goods and services -  others do this only using the 45 classes of

the Nice Classification

Mix-and-match approach to AI techniques -  traditionally AI has been divided into to

factions: rule-based and statistical -  all our competitors are also either-or -  both have their advantages and

disadvantages -  unlike the mainstream, we’re flexible and

use both as we see fit, to maximize their benefits

Rule-based vs. statistical -  easy to get started -  understandable -  easy to modify - modified manually -  can only handle

known cases well -  requires clean

inputs

-  requires good data -  impenetrable -  hard to revise -  can learn - much better at

handling noisy or unforeseen data

Thank you! Questions?