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About Timber Stacks
The company must also provide data to the firms making markets on those events.
“If we just sold the data to Kalshi in order to list the markets but no one was coming in and placing liquidity, there’s no point in them listing the markets,” Monk said. “We also need to supply the data to the market makers to inform their models.”
Catalist initially received a list of fewer than 10 potential market makers from Kalshi. It has since completed agreements with close to 20 and is engaging with approximately another 20.
About Timber Stacks
The shift means that rather than spending their time pricing and managing established markets, traders can now apply their expertise where human judgement has the greatest value, including developing and testing new products. AI removes many of the practical limits on what can be offered and priced, and manages the resulting scale and complexity. The result is greater efficiency for Kambi and a better service for its partners and their customers.
“To this point, sportsbook product creation has largely been guided by a trading department’s ability to profitably price and risk-manage certain bet offers,” Lamb says. “AI trading lifts those limitations, while also enabling that existing human expertise to be leveraged more effectively.”
The 2026 tournament demonstrated why Kambi believes this total integration of AI is necessary. Sportsbooks are no longer built primarily around match results and traditional pre-match markets. Bettors increasingly expect to construct wagers around individual players and specific moments within a game.
What is Timber Stacks?
“[At] above roughly 150 players per manager, personal knowledge stops scaling. The fix is not fewer players or more managers – it is showing each manager which few accounts actually need them today,” she added.
Satisfaction with existing tools scored an average of 6 out of 10. Co-author Gali Hartuv, CEO and co-founder at WarriorLab described this “middling satisfaction” as “the most expensive kind”.
While VIP managers welcomed AI for prioritising their workload, the report suggested they remained cautious about delegating a final judgment to opaque automated systems.
