Case Study
How Inflectiv Made the Data Behind AI Agents Trustworthy
Learn how they used Walrus to help AI agents make intelligent decisions.
AI agents often fail not because the models are weak, but because the data pipelines feeding them are unverifiable. Apps building in critical industries, like DeFi and AI, need data that is traceable, yet no trust layer exists between data ingestion and agent execution.
Walrus gave Inflectiv, the intelligence infrastructure for AI agents, the tool to close that gap, replacing centralized storage with cryptographically verifiable, immutable data. Now enterprises and Web3 systems can finally trust what their agents know—and prove it.
vs AWS S3
on Walrus
weeks
Good decisions start with good data
Clean, reliable intelligence is what separates agents that make smart decisions from those that don’t. Inflectiv transforms messy, unstructured data—like PDFs, internal docs, web pages, sensor data—into structured, validated datasets that power AI agents in production systems. In order to do so successfully, they needed to guarantee data powering agents hadn’t been altered, could be traced back to its original source, and would hold up in high-stakes industries like DeFi and AI. As AI agents take on higher-stakes decisions, the ability to independently audit what data they acted on is quickly becoming an expectation for both enterprise and regulated environments.
Store. Verify. Prove.
Walrus delivered exactly that, combining decentralized storage with onchain provenance in a single, integrated stack. Every raw file ingested by Inflectiv is anchored as an immutable blob on Walrus, assigned a cryptographic blob ID, and registered as an object on Sui, creating an unbroken chain of custody from raw data all the way through to agent execution. Where centralized storage could only offer platform trust, Walrus offered something far more durable: independent, verifiable proof that the data is exactly what it claims to be.
“Walrus was surprisingly straightforward to integrate. The publisher API is clean, and pairing it with Seal for per-file encryption gave us decentralized access control that would have taken weeks to build on AWS.”
Inflectiv Engineering Team
Now verifying over 4,000 datasets
Since integrating Walrus, Inflectiv has stored over 4,000 datasets. The architecture shift has been equally significant. What once relied on centralized cloud infrastructure now runs on a trust-minimized stack where every dataset version is immutable, every agent decision is traceable, and every source can be independently verified.
Learn how Walrus powers verifiable AI
Learn how to get started on Walrus
