AI can produce an answer. Financial systems need a way to verify it.
I've been thinking about what happens when AI agents move beyond answering questions and start making financial decisions.
Imagine an AI agent evaluating a DeFi protocol. Before acting, it needs to understand more than the current balance. It may need historical transaction activity, protocol fees and changes over time.
But how can an application trust the calculation behind that information?
This is the problem Space and Time is working to address.
Its Proof of SQL technology allows applications to query structured data and receive cryptographic proof that the underlying committed data and supported SQL computation are correct.
I find three applications particularly interesting:
AI: An agent could use a proven query result showing a protocol's recorded fees over a specific period when evaluating its activity.
Tokenization: Applications can verify calculations involving asset holdings, cashflows and valuations, including information used in NAV reporting.
DeFi: Uniswap v4 hook templates can use verified historical trading activity to determine loyalty-based swap fee discounts.
These aren't just three separate blockchain narratives. They share one important requirement: applications need dependable data before they can make decisions.
And there is a practical network role for $SXT It is used to pay for network workloads and is staked to support validator security.
What interests me most is the shift from simply accessing data to being able to prove how an answer was produced.
Because in financial infrastructure, an answer is only as useful as the evidence behind it.
@SpaceandTime
Paid promotion: This content is created as part of the Binance Square × Space and Time creator campaign.
Purchasing SXT is risky. You are encouraged to DYOR 👀 and to consult professional advice before buying SXT or any other cryptocurrency.
#SXT
#sxt @SpaceandTime
I've been thinking about what happens when AI agents move beyond answering questions and start making financial decisions.
Imagine an AI agent evaluating a DeFi protocol. Before acting, it needs to understand more than the current balance. It may need historical transaction activity, protocol fees and changes over time.
But how can an application trust the calculation behind that information?
This is the problem Space and Time is working to address.
Its Proof of SQL technology allows applications to query structured data and receive cryptographic proof that the underlying committed data and supported SQL computation are correct.
I find three applications particularly interesting:
AI: An agent could use a proven query result showing a protocol's recorded fees over a specific period when evaluating its activity.
Tokenization: Applications can verify calculations involving asset holdings, cashflows and valuations, including information used in NAV reporting.
DeFi: Uniswap v4 hook templates can use verified historical trading activity to determine loyalty-based swap fee discounts.
These aren't just three separate blockchain narratives. They share one important requirement: applications need dependable data before they can make decisions.
And there is a practical network role for $SXT It is used to pay for network workloads and is staked to support validator security.
What interests me most is the shift from simply accessing data to being able to prove how an answer was produced.
Because in financial infrastructure, an answer is only as useful as the evidence behind it.
@SpaceandTime
Paid promotion: This content is created as part of the Binance Square × Space and Time creator campaign.
Purchasing SXT is risky. You are encouraged to DYOR 👀 and to consult professional advice before buying SXT or any other cryptocurrency.
#SXT
#sxt @SpaceandTime
