The AI bull case for PETs: Nillion deep dive
Thread1,272 words
Bullish call$NIL−88%since listing, moved against the callHow it played out ↓Deep dive on why AI needs data confidentiality and how Nillion's MPC differs from traditional schemes, with non-linear computation, input-independent pre-processing, non-interactive operation and information-theoretic security. Uses the Ritual partnership as a case study.
Key claims
Nillion MPC supports non-linear operations with information-theoretic security
Pre-processing is decoupled from inputs
OpenAI raised $6.5B at >$150B
The AI Bullcase for PETs
OpenAI just raised $6.5B at a valuation of >$150B and the AI hype will only accelerate in 2025.
These huge amounts of capital that AI attracts are starting to spill over into crypto, which creates generational opportunities.
Thesis & deep dive on @nillion. ↓
In this post we will cover:
➊ The Need for Privacy in AI
➋ Meet the Nillion Network
➌ Nillion MPC and Why It Matters
➍ The Ritual Case Study
➎ The Long-Term Vision
➏ Conclusion
Ready for alpha anon? ↓
➊ The Need for Privacy in AI
While the opportunities are huge, all the noise and vaporware makes identifying the winners hard.
Especially in a sector that is defined by a high degree of complexity and a lot of big promises (like AI).
What is a fact however, is that to unleash the full power of AI across many verticals, data confidentiality and security is not just a feature but rather a requirement.
In many cases, AI/ML models need to work with high-value data, whether that is financial data, medical data, or other forms of sensitive, personal data. That hold especially true, if we're talking about personalized AI, which will be a major trend in the months and years to come.
That this data should be encrypted and not accessible by any third party seems evident if we're thinking about AI models that are specialized on analyzing medical data, but is also relevant if we think about AI-powered on-chain automation strategies, sniper bots, etc., where confidentiality is key to prevent users from being frontrun.
➋ Meet the Nillion Network
That brings us to @nillion, a decentralized network for secure computation, specialized on handling high-value data.
High-value data refers to critical information with significant importance across various sectors of society, which includes financial trading data, healthcare records, identity-related information, etc.
Historically, handling this type of data is a complex endeavour and key challenges in handling high-value data include:
➤ Secure storage: Data encryption safeguards information at rest but creates limitations when it needs to be processed.
➤ Computation on encrypted data: The traditional decrypt-compute-reencrypt cycle exposes data to security risks and inefficiencies.
➤ Decentralized data management: While decentralization ensures transparency and resilience, managing high-value data across distributed nodes introduces complexity.
@nillion overcomes these challenges using an optimized Multi-Party Computation (MPC) scheme that enables the secure storage and processing of data without decryption, ensuring confidentiality even during computation.
The network itself is based on a dual architecture of two parallel, interdependent networks: a coordination layer and an orchestration layer.
➤ The NilChain network coordinates payments for storage operations and blind computations performed on the network.
➤ The Petnet leverges PETs such as MPC to protect data at rest and to enable blind computations that can operate on that data.
The overall @nillion operates without a global shared state or consensus on order.
Instead, it is specifically designed to support storage of private high-value data and computation over that data while decentralizing trust among the nodes in the network.
➌ Nillion MPC and Why It Matters
Okay cool but how does @nillion differ from other MPC solutions in the market?
To understand Nillion, we have to take a look at how traditional secure multi-party computation protocols work and what their limitations are.
Many of them rely on linear secret sharing schemes that often do not rely on cryptographic assumptions, as these are the most straightforward to implement correctly.
However, basic MPC schemes typically restrict participants to linear operations or require synchronous communication during computation.
@nillion's MPC protocol drastically diverges from traditional schemes by enhancing privacy, enabling non-linear computations, and improving efficiency of the overall system.
This makes it particularly well suited for more complex and advanced, privacy-preserving blockchain applications where security is paramount (e.g. in the AI/ML sector).
So let's have a closer look at what makes Nillion MPC unique:
➤ Linear vs. Non-linear Computation: Traditional MPC handles only linear operations and slows down with non-linear tasks. Nillion’s MPC efficiently supports non-linear operations, ideal for complex blockchain computations like smart contracts, while maintaining privacy.
➤ Pre-processing Efficiency: Traditional MPC’s pre-processing is input-dependent and resource-intensive, adding latency. Nillion’s MPC decouples pre-processing from inputs, speeding up preparation based on the number of inputs, enhancing performance for high-throughput systems.
➤ Asynchronous, Non-interactive Computation: Traditional MPC requires continuous communication between participants, causing delays. Nillion’s MPC is non-interactive, allowing independent computation and reducing latency, fitting decentralized blockchain environments.
➤ Enhanced Security: Nillion’s MPC offers Information-Theoretic Security (ITS), which means that even with unlimited computing resources, an adversary cannot breach the protocol's security. This is crucial for privacy-focused blockchain apps in many of the before-mentioned verticals (including AI/ML), ensuring the protection of sensitive user data.
➍ The Ritual Case Study
How this enables AI-powered use cases is evidenced by @nillion's recent partnership with @ritualnet a decentralized AI infrastructure network, that aims to enables secure AI inference on sensitive data.
By integrating Nillion’s blind computation technology, @ritualnet can process private inputs and AI models without exposing any data, offering a breakthrough in privacy-preserving AI.
That has various benefits to the overall system:
➤ Data and model privacy: Ensures both user inputs and AI models remain confidential during computation, crucial for personalized AI and sensitive data processing.
➤ Enterprise adoption: Solves privacy concerns, allowing businesses to use AI securely with sensitive data.
➤ Secure model sharing: Protects intellectual property by enabling the sharing of proprietary AI models without exposing core algorithms.
➤ Decentralized collaboration: Promotes open, collaborative AI development by preventing single entities from controlling models.
The integration will enable various use cases, including:
➝ Secure AI agents and chatbots for private intent classification
➝ Privacy-preserving information retrieval for generative AI systems
➝ AI in healthcare, IoT, and federated learning with robust data privacy
➝ Private financial forecasting that secures proprietary models & user data
➝ Advanced anonymization for secure interactions with generative AI
➎ The Long-Term Vision
Aside @ritualnet, Nillion has also partnered with @NEARProtocol and @Aptos, two leading general-purpose ecosystems within the broader DeAI sector, in which builders can now seamlessly plug into Nillion's blind computing capabilities.
What is also important to note here, is that while the focus of this post lies on Nillion's MPC scheme, Nillion aims to become humanity’s first Blind Computer.
Powered by a decentralized network of nodes, Nillion enables blind computation through the coordination and orchestration of privacy enhancing technologies (PETs) such as multi-party computation (MPC), fully homomorphic encryption (FHE) and zero-knowledge proofs (ZKP).
The ultimate vision is that this Blind Computer becomes the decentralized internet’s base layer for all private data.
➏ Conclusion
In summary, @nillion's MPC protocol offers superior privacy, efficiency, and scalability for blockchain use cases than any other MPC solution in the market.
By supporting non-linear operations under information-theoretic security guarantees, it ensures that sensitive data remains protected during processing, while optimized pre-processing and non-interactive computation phases reduce communication & computation overhead, aligning with crypto's decentralized and asynchronous nature.
The plans to expand the protocol into a coordination layer for any PET are ambitious but definitely bear huge potential, especially as technologies such as MPC can be seamlessly combined with ZK and FHE to allow for fully customized implementations of these approaches, optimized for specific use cases.
All of this makes @nillion especially well-suited for handling complex, large-scale applications across AI/ML and adjacent sectors (incl. DeFi), where rapid and secure transaction processing is critical (another area where traditional MPC models often fall short).
Don't fade @nillion anon.
DYOR.
Not convinced yet?
Watch this. ↓
x.com/nillionnetwork/status/1837144689960702402
For a more comprehensive overview of the DeAI space, also check my landscape post below! ↓
x.com/zerokn0wledge_/status/1844020745464422508
3 more images on X
How the call played out · since 10 Oct 2024
Prices as of 23 Oct 2026This piece takes a view on $NIL, so that move is read against the call.
−88%
Moved against the call · since it listed on 25 Mar 2025, 5 months after this piece
- At listing
- $0.725
- Now
- $0.0841
- vs BTC
- −88%
- After 1 month
- −47%
- After 3 months
- −61%
- After 1 year
- −95%
- High since
- 0.0% 25 Mar 2025
- Low since
- −96% 02 Aug 2026
Since then
Zero has written 12 more pieces on Nillion and $NIL since this one.
- Nillion MPC plus io.net GPUs: a private decentralized compute stack for AIOn Nillion
- Nillion as the orchestration layer for privacy-enhancing technologiesBullish call on $NIL
- io.net x Nillion: private decentralized compute stack for personalized AICovers $NIL
- io.net as a PMF case study in crypto, and why the Nillion tie-up mattersCovers $NIL
Daily closes in USD from DefiLlama and Yahoo Finance. Only a bullish or bearish thesis is read as a call; explainers, maps and mentions are context. Not financial advice.