SPEX: Verifiable AI for the Real World

LLMs and AI agents are making more decisions than ever—but how do we verify that they’re doing what they say?

Enter SPEX (Statistical Proof of Execution) by Warden Protocol.

It’s a lightweight, sampling-based framework to prove that a computation (even non-deterministic ones like AI inference) was actually executed, without re-running the entire process.

Why it matters:

Cheaper & faster than ZKML, FHE, or MPC

Handles LLMs, float arrays, embeddings, and even agentic plans

Resilient against lazy or adversarial solvers

Open-source Python lib (github.com/warden-protocol/warden-spex)

Key concept:

Hash computational states into Bloom filters.
Sample + verify at runtime.
Tune confidence level (X%) vs cost.

Read the paper: arxiv.org/abs/2503.18899

Deep dives:

SPEX as an AI firewall https://wardenprotocol.org/blog/spex-the-firewall-for-ai

Verifiability in the age of black-box models https://wardenprotocol.org/blog/spex-verifiability-in-the-age-of-black-box

Defending against manipulation
 https://wardenprotocol.org/blog/spex-combating-ai-system-manipulation

Trust but verify.

Then do it statistically.

#ZK #LLM #AIInfra #WardenProtocol #Web3Dev #SPEX