ritual

EVM++ Sidecars Explained Simply

Ritual extends the EVM with modular sidecars for powerful compute. Unlike Ethereum, where precompiles live in the client code, Ritual runs them as separate containers that scale in parallel.

Supported Sidecars:
- Classical ML: Run tree- and regression-based models.
- LLM Inference: Power advanced language tasks with LLMs.
- ZK Proofs: Generate verifiable zero-knowledge proofs.
- TEE Execution: Secure compute in trusted environments for AI, APIs, and agents.
- Chain Abstraction: Read and soon write state across other blockchains.

#ritual

Which #AI crypto narrative do you think will lead the rest of 2025?

A) Agentic Economies: #VIRTUAL , $FET , #RITUAL

B) Decentralized Compute: TAO , RENDER , $ICP

C) AI x DeFi: #VIRTUAL , #sdao

D) Infrastructure: TAO, GRT, $NEAR , AIOZ

Which narrative excites you most?

Ritual’s Modular Storage Explained

Ritual introduces modular, storage-agnostic infrastructure that connects smart contracts with both Web2 and Web3 data layers, enabling secure, cost-efficient, and flexible access to large AI models and beyond.

Ritual fixes this with modular, storage-agnostic design. Instead of locking into one system, Ritual uses repositories that can plug into multiple storage layers.

#ritual #ai #tee

Ritual Use Cases Review

Use Ritual EVM to build & monetize AIGC in infinite AI worlds, on-chain agents, and dynamic DeFi adapting in real time.

Build infinite worlds:
Create a new class of consumer applications built around on-chain monetization of AIGC, prompts, and even models themselves

Build autonomous agents:
Launch and monetize on-chain agents that act and interact with the chain with total independence.

Build dynamic DeFi:
DeFi reimagined with transparent models that enable protocols to autonomously adapt to market conditions in real-time

Build fautonomous agents:
Launch and monetize on-chain agents that act and interact with the chain with total independence.

Build anything & everything:
Ritual is EVM-compatible and designed to supercharge applications at the intersection of Crypto x AI. What will you build?

#ritual

Ritual’s Gadgets for Verifiable AI

Ritual brings computational integrity to AI — making sure outputs are provably correct, without blind trust in centralized operators.

Supported Gadgets:
- ZK Machine Learning: Strongest cryptographic security, but costly and slow.
- Optimistic ML: Assumes correctness, checks only if disputed, cheaper and scalable.
- Trusted Execution Environments: Fast and private, but relies on chip vendors.
- Probabilistic Proof ML: Cheap, statistical verification for heavy workloads like LLMs.

#ritual