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Space and Time: where AI agents meet verifiable onchain data

Posted on September 6, 2026 By Emily Chen No Comments on Space and Time: where AI agents meet verifiable onchain data

Space and Time: Where AI Agents Meet Verifiable Onchain Data

September 6, 2026 – 4:07 pm

(Photo by Scott Dykstra)

Credit: Scott Dykstra

Introduction to Space and Time

Space and Time was the first Web3 company to secure funding from Microsoft’s M12 venture arm, a backing that propelled it into the spotlight. Since then, the company has launched its purpose-built SXT Chain and expanded its Proof of SQL technology across various sectors including:

  • DeFi (Decentralized Finance)
  • Institutional finance
  • AI (Artificial Intelligence)

In this interview, Scott Dykstra, Space and Time’s co-founder and CTO, discusses the team’s learnings since mainnet launch, where AI agents are already utilizing verifiable onchain data, and how their strategy is evolving with blockchain infrastructure maturity.

Purpose-Specific Chain vs General L1 Competitor

Choosing to build a purpose-specific chain was essential to address a specific technical challenge for Ethereum: enabling smart contracts to query verifiable data. Space and Time’s Proof of SQL technology necessitates a dedicated chain of nodes alongside Ethereum, working in tandem to verify Ethereum data and return query results back to customer smart contracts—similar to an oracle for data querying.

While rollups like Base, Stripe’s Tempo, Circle’s Arc, Robinhood Chain, etc., have gained traction, Space and Time thrives as it is EVM-focused. As more developers join these EVM chains, Space and Time can support them as the onchain database.

Performance of Proof of SQL

Space and Time’s Proof of SQL lets Prover nodes process queries and generate proofs in under a second. While most client queries remain sub-second—particularly for constant, daily workloads like checking collateral before trade execution—more complex queries over extended Ethereum transaction histories can lead to slight delays. These queries are generally executed on-demand by clients.

An example of such a query is a lending protocol calculating rewards by aggregating total deposits from a specific wallet over time.

AI Agents and Smart Contracts

Smart contracts are increasingly serving as controls or safeguards for autonomous AI agents. Currently, we see users utilizing smart contracts to control capital allocations to sub-accounts, pioneered by Hyperliquid. This allows the contract to query Space and Time’s data to assess an agent’s trading performance over a period before executing actions like rescinding or adding capital to that agent’s sub-account.

In the lending space, we’re witnessing more vault management with Space and Time’s data providing transparency and security for onchain operations.

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