Janice

What I like about Ritual is that it doesn’t ask developers to relearn everything. You still call models like you would with a normal AI API. The difference is that underneath, you get decentralization, privacy guarantees, and censorship resistance by default.

Ritual provides a powerful compute layer that any blockchain or app can tap into. Instead of every chain trying to run heavy workloads themselves, they can offload AI inference, proofs, and specialized computation to Ritual’s optimized nodes. Ritual as a backend Other blockchains can integrate Ritual through messaging or via Infernet, Ritual’s compute framework. This allows chains to outsource things like: • ZK proof generation • AI model execution • Secure TEE computations …while keeping their own chains lighter and more efficient. Who benefits most Ritual is built for: • High-performance chains that need strong prover networks • RaaS platforms running custom rollups with AI or ZK workloads • IP monetization platforms where models and digital assets are sold with verifiable ownership Why this matters Ritual is designed to support any kind of computation; now and in the future. As new workloads emerge, Ritual adapts. This creates a win-win system: • Other chains get scalable, high-performance compute • Ritual earns demand and fees across many ecosystems

Ritual: The On-Chain Compute Layer Every Blockchain Can Call Ritual is designed to be a chain that other blockchains and apps “call into” when they need heavy or specialized computation like AI inference, proofs, or TEE execution, instead of trying to run everything directly in a normal smart‑contract VM. What this means in practice A dApp on another chain could call Ritual to run a large model, generate or verify a proof, or execute sensitive logic in a TEE, then bring back a verifiable result to finalize logic on its home chain. This lets existing ecosystems keep their user base, liquidity, and contract logic, while plugging into Ritual whenever they need more expressive, AI‑heavy, or verification‑intensive computation than their native environment can efficiently handle. Gritual

We raised $500M at an $11B valuation to transform how people interact with technology.