Data privacy concerns
Sensitive data is exposed to third-party models and opaque processing pipelines.
0G Singapore
The Infrastructure
The Infrastructure
Behind Trusted AI.
Deploy AI with infrastructure built for privacy, verification, and compliance.
Built for the institutions where trust is not optional.
The problem
Today's AI infrastructure wasn't designed for enterprise trust.
Most AI stacks optimize for speed and scale. The properties that regulated organizations depend on were never part of the design.
Vendor lock-in
Proprietary stacks make it costly to move models, data, or workloads elsewhere.
Black-box inference
Results arrive with no record of how, or on what basis, they were produced.
Limited auditability
Teams cannot reconstruct what a model did, or prove it to a regulator.
Regulatory uncertainty
Rules for AI are tightening, and most systems were not built to comply.
The platform
One platform. Four trusted infrastructure layers.
Each layer solves one requirement for trusted AI. Together they form a single, coherent foundation.
Private Compute
Run AI workloads without exposing sensitive data. Inference runs inside hardware trusted execution environments that return a signed attestation of exactly what ran.
Decentralized Storage
Store models and datasets with cryptographic integrity. Durability comes from erasure coding, with nodes continuously challenged to prove they still hold the data.
Persistent Memory
Enable AI agents with long-term, verifiable memory.
Verification Layer
Prove every AI action, inference, and data source. Hardware attestation, optimistic verification, and zero-knowledge proofs; every interaction cryptographically signed.
How it works
From application to permanent record.
A request flows through each layer, gaining privacy, memory, integrity, and proof along the way.
AI Application
Your model, agent, or service.
Private Compute
Runs the workload without exposing its inputs.
Memory Layer
Persists the context an agent can rely on.
Storage Layer
Holds models and data with cryptographic integrity.
Verification Layer
Attests to every action and inference.
0G Chain
An EVM-compatible blockchain anchors the record for independent audit.
AI Safety
Build AI you can trust.
Every model. Every inference. Every decision. Verifiable by design.
Most organizations can only state their commitment to responsible AI. 0G provides the infrastructure to prove it.
AI Alignment
Keep model behavior accountable to the people it serves.
Auditability
Reconstruct any decision, end to end, whenever it is questioned.
Traceability
Follow every output back to the data and the steps that produced it.
Research & ecosystem
Advancing trusted AI together.
0G Singapore convenes governments, universities, and enterprises around a shared standard for trusted AI, through workshops, certification, and applied research.
Academic Research
Joint work with universities on verifiable AI, including the NTU Singapore × 0G research hub for decentralized AI.
Government Partnerships
Working with agencies to build AI capacity they can stand behind.
University Programs
Curriculum and resources that bring trusted AI into the classroom.
Enterprise Innovation
Applied pilots that take trusted AI from proof to production.
Grants & Ecosystem Growth
Milestone and retroactive grants, with priority for open-source work.
Hackathons
Hands-on events where new ideas for trusted AI take shape.
0G Accelerator
Funding, mentorship, and go-to-market support for AI founders.
Certification
Professional certification that sets a clear, credible bar for trusted-AI practice.
Training & Workshops
Practical programs for public-sector and enterprise teams, delivered in the region.
Deployment patterns
Repeatable ways to put trusted AI into production.
Capability patterns drawn from how each kind of organization adopts the platform, not case studies.
Singapore proof point
NTU Singapore × 0G
In November 2025, Nanyang Technological University (NTU) Singapore and Zero Gravity established a S$5M joint research hub for decentralized AI, advancing decentralized model training and blockchain-integrated model alignment. The four-year program targets applied pilots in finance, healthcare, and smart infrastructure, moving trusted AI from research into real deployment.
Government
- Problem
- Citizen data cannot leave national control.
- Approach
- Sovereign AI on private compute with verifiable storage.
- Result
- Public services powered by AI that stays auditable and in-country.
University
- Problem
- Research needs reproducible, tamper-evident results.
- Approach
- Verification and storage layers that record every step.
- Result
- Findings that can be independently checked and built upon.
Enterprise
- Problem
- Internal AI must respect data boundaries and policy.
- Approach
- Private compute with traceable memory and access controls.
- Result
- Copilots and automation that pass internal and external audit.
Research
- Problem
- Model claims are hard to verify at scale.
- Approach
- Attestation across inference, data, and model provenance.
- Result
- Safety evaluations backed by evidence, not assertion.
Resources
Go deeper.
Documentation, research, and code from across the 0G ecosystem.
Developer Docs
Guides and references to build on the platform.
docs.0g.aiLatest Research
Publications and joint work from the 0G research group.
research.0g.ai0G Foundation
The steward of decentralized AI as a public good.
0gfoundation.aiBlog
Announcements, research notes, and deep dives.
0g.ai/blogSecurity
Audit practices and the platform bug bounty program.
docs.0g.aiGitHub
Open-source repositories and reference code.
github.com/0gfoundation
Company
About 0G Singapore
0G Singapore leads 0G's programs across the region: running workshops and certification, and partnering with government agencies and universities to advance trusted AI. It operates as part of the global 0G Foundation, the steward of decentralized AI, whose mission is to make AI a public good.
Ready to build trusted AI?
Let's create the next generation of AI infrastructure together.