We recently secured $20,000 in angel funding to supercharge our growth.
Reality lives in ranges and we are committed to building that.
#Predictionmarket
WHEN is evolving, we started earlier with small markets.
Now we are rebuilding the system as an infrastructure layer around a clearer direction which is a belief system market for real world outcomes.
GEN Z TURNS TO CRYPTO AND BETTING FOR WEALTH
Many Gen Z investors are turning to high-risk assets to reach financial goals, according to a study by Northwestern Mutual.
The survey found 80% of Gen Z feel financially behind and believe speculative investments can help them build wealth faster than traditional strategies.
About 32% are invested in or considering crypto, while a similar share are participating in sports betting and prediction markets.
Motherlode showed how ranges can change interaction with outcomes.
What gets interesting is when ranges stop being a single product and become a primitive creators can use.
SOVs are probabilistic by nature.
You don’t know WHEN the hit comes. You only know it lands somewhere.
That’s exactly why SOVs like @ore and @Godlsupply made sense for our first range based product.
We didn’t build WHEN on @solana just for one market.
Motherlode prediction is our first product, not the destination.
Range based predictions open the door to new ways of interacting with outcomes.
$ORE $GODL
We’ve been answering a lot of questions about overlapping ranges on our ML predictions.
They don’t overlap. Final hit lands in one range. Transparent settlement onchain.
Appreciate all the feedback so far.
https://t.co/bDCEkNRQQv
$ORE
We are live.
WHEN is a new kind of prediction market built for uncertainty not yes/no outcomes.
Today we’re launching our first markets:
Motherlode range predictions for
• GODL
• ORE
Predict in ranges not binaries.
https://t.co/uSJ7xs6fPq
The future isn’t binary. It’s a range of outcomes.
$ORE $GODL #WHEN
Most prediction markets force the future into a YES/NO box.
WHEN doesn’t.
Our first live product - Motherlode hits prediction lets you predict in ranges not binary with everything verifiable on-chain.
Because forcing precision is the mistake.
It always lands somewhere.