OpenIO

We are building a unified platform for private computation — a complete environment where developers and organizations can discover, build, and deploy privacy-preserving models using zero-knowledge proofs (ZK), fully homomorphic encryption (FHE), and indistinguishability obfuscation (iO). Today, these technologies exist in fragmented ecosystems with incompatible tooling, steep learning curves, and no standard way to integrate or deploy them. Our platform solves this by offering a shared hub of privacy models, circuits, functions, and sealed logic modules that can be reused, remixed, or extended by anyone.

Through a dual-mode builder that supports both visual workflows and traditional code, we make it possible to compose encrypted, obfuscated, and verifiable logic without requiring cryptography expertise. Developers can drag-and-drop privacy primitives, stitch together hybrid pipelines, or work directly in a full-stack SDK that abstracts all cryptographic complexity. Each workflow is automatically packaged into sealed or encrypted artifacts, ready for execution across cloud, edge, on-chain, or local environments.

At its core, our platform introduces a consistent standard for privacy-preserving computation — something the ecosystem has lacked. By unifying ZK, FHE, and iO under a single workflow and runtime, we eliminate the need for bespoke tooling, custom integrations, or specialist teams. This enables secure analytics, private AI inference, sealed logic execution, verifiable processing, and encrypted data flows to be built and deployed as easily as modern software applications.

Our mission is to make advanced privacy technologies accessible, composable, and operational at scale. By providing a single platform for the entire lifecycle of private computation — discovery, building, and deployment — we empower developers and partners to protect sensitive data, proprietary algorithms, and AI models with a straightforward, consistent, and production-ready stack.

Our project is built as a modular privacy-compute platform that unifies three traditionally separate cryptographic technologies — ZK, FHE, and iO — into a single workflow for discovering, composing, and deploying private computation.

At the core, we built an abstraction layer that standardizes how privacy primitives interact. The system exposes a simple API and SDK that lets developers treat ZK circuits, FHE functions, and iO-sealed modules as interchangeable building blocks. Under the hood, each primitive is compiled, packaged, and executed through its own optimized backend, but fully coordinated by a shared runtime that manages data flow, proofs, sealing, and encrypted evaluation.

The project consists of three major components:

1. The Models Hub A centralized registry that stores reusable privacy components — ZK circuits, FHE operators, iO logic modules, and hybrid pipelines. We implemented this as a metadata-driven store backed by object storage and a lightweight indexing layer. Developers can publish, fork, version, and retrieve models through REST and SDK interfaces.

2. The Builder (Visual + Code) A dual-mode environment inspired by n8n and Remix. • The visual builder converts drag-and-drop nodes into an intermediate representation that maps directly to privacy primitives. • The code editor (JS/TS first) compiles to the same IR, ensuring both modes stay in sync. We built the IR as a graph structure that can express ZK → FHE → iO pipelines, including validation rules, expected inputs, and execution order.

3. The Runtime & Deployment Engine A unified execution environment that evaluates: • ZK components through a proof generator/validator backend • FHE components through encrypted evaluation drivers • iO components through a sealed-logic execution sandbox The runtime orchestrates the order of operations and guarantees that logic stays sealed and data stays encrypted throughout. We made deployment targets pluggable: cloud workers, local environments, secure enclaves, and eventually on-chain execution.