| Key Points: – Nillion unveils nilDB, nilAI, and nilVM to power encrypted app and AI development. – nilDB enables real-time computation on encrypted data using secret sharing. – nilAI supports private machine learning via MPC, TEE, and Python-based tools. |
Nillion Reveals Full Blind Tech Stack to Enable Encrypted AI and App Development, introducing a modular suite of tools — nilDB, nilAI, and nilVM — that empowers developers to build privacy-preserving applications without cryptographic expertise.
At the core of Nillion’s privacy-first infrastructure, nilDB enables real-time computation on encrypted data, while nilAI supports private machine learning using MPC, TEEs, and custom Python libraries. nilVM provides a dedicated developer environment with domain-specific tools for secure app development.
Together, these components are orchestrated via an integrated layer combining MPC, TEE, FHE, and encrypted storage, facilitating use cases from LLM inference to private DeFi. Live deployments include Skillful AI, Rainfall, Mailchain, and others handling regulated or sensitive datasets, positioning Nillion as a foundational layer for secure computation in Web3 and enterprise AI.
nilDB, nilAI, nilVM Power Privacy-First Apps in Web3 and Enterprise
Nillion has disclosed technical details of its Blind Tech Stack, a suite of technologies designed to facilitate privacy-preserving computation across various Web3 and enterprise applications.
The components — nilDB, nilAI, and nilVM — form the foundation of what the company describes as a platform where privacy is the default, not a feature.
These tools enable developers to work with encrypted data without requiring expertise in cryptography or compromising performance.
Encrypted Database: nilDB Enables Computation Without Decryption
nilDB is a decentralized, encrypted NoSQL database designed for secure storage and querying of sensitive data. Unlike systems such as Filecoin or IPFS, nilDB supports real-time computation on encrypted data.
- The database uses secret sharing to distribute data fragments across multiple nodes, ensuring no single party can access the original dataset.
- Use cases include privacy-preserving health data analysis, encrypted social graphs, and secure storage of identity credentials.
The platform is already in use by firms including ZAP, Fulcra, Healthblocks, and Humanity, each handling sensitive data in regulated environments.
nilAI Powers Encrypted AI Inference and Learning
nilAI is Nillion’s dedicated suite for enabling machine learning on encrypted data, supporting secure model training and inference in environments where data privacy is critical.
Key components include:
- AIVM (AI Virtual Machine): Executes encrypted inference using Multi-Party Computation (MPC), ensuring that even participating nodes lack visibility into input or output data.
- nada-AI: A Python library modeled after frameworks like PyTorch, allowing for small-scale AI model development on encrypted datasets.
- nilTEE: A Trusted Execution Environment (TEE) layer enabling large language model (LLM) operations at scale without compromising privacy.
Notable research and implementation partners include Meta AI, with additional deployments by Virtuals, Verida, and Capx.
nilVM: Developer Toolkit for Privacy-First App Development
nilVM serves as the developer environment for writing privacy-preserving applications. It uses a domain-specific language called Nada, built on Python syntax, and offers access to encrypted computation tools and libraries.
Features include:
- Linear Secret Sharing Schemes (LSSS) for secure computation.
- Libraries such as nada-numpy, nada-data, and nada-AI to support faster prototyping.
- Integrated storage APIs for end-to-end encrypted workflows.
Live deployments include:
| Project | Description |
|---|---|
| Skillful AI | Private RAG models |
| Rainfall | Federated learning |
| Mailchain | Encrypted email storage |
| Kayra | Dark pool trading |
| ChooseK | DeFi order books |
| BattleshipX | Encrypted P2P gaming |
The SDK has been downloaded 961 times, and more than 100 open-source contributors have joined the project.
Orchestration Layer Integrates Privacy Technologies
Nillion’s Orchestration Layer coordinates multiple privacy-enhancing technologies — MPC, TEE, Fully Homomorphic Encryption (FHE), and nilVM — into a modular system. The integration allows developers to build custom privacy workflows, such as:
- Performing LLM inference in a TEE,
- Retrieving context from encrypted databases using nilDB,
- Executing logic via nilVM.
Quick Take
The orchestration allows developers to build privacy-first applications without compromising performance or data security.
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