INTELLIGENT SCIENCE, DECENTRALIZED
Science is at an inflection point. AI reads signals at scale, but most models are black boxes: powerful yet opaque, unable to explain why. Health data is also locked in silos, out of reach for patients and researchers.
LIFE Networks is building a new infrastructure for decentralized science, founded on three core pillars: explainable neuro-symbolic intelligence, verifiable security with compute-to-data in TEEs, and consented multimodal health data.
This architecture enables true data sovereignty by design. Data stays where it lives, code moves to it—allowing individuals to own their health data and control how it is used, rewarded, and revoked.
Explainable Intelligence
The Problem:
Large Language Models (LLMs) are powerful correlators, but they struggle with multi-step inference and factual verification.
They guess instead of reasoning.
Our Solution: The Wisdom Graph System (WGS)
LIFE Networks' WGS unites the neural layer's pattern recognition with the symbolic layer's logical structure. It creates an AI that not only understands patterns but also explains them.
Core Principles
- Neural Layer - Detects statistical patterns from multimodal data (blood pressure, glucose, gene sequences, MRI signals).
- Symbolic Layer - Interprets those patterns into structured ontologies and causal rules.
- Evidence Graph - Links cause → mechanism → outcome, turning AI inferences into traceable logic.
The Wisdom Graph System (WGS)
WGS's reasoning engine integrates deduction, induction, and abduction, establishing a verifiable framework for compositional reasoning. It unites comprehension with correlation, transforming static data into actionable, explainable knowledge.
Traditional LLMs guess - WGS justifies. LIFE's AI doesn't hallucinate; it reasons.
Capabilities Enabled
- Multimodal Data Interpretation: Correlates genomic, clinical, and behavioral data.
- AI-Curated Drug Discovery: Generates hypotheses grounded in verified biomedical evidence.
- Personalized Treatment Design: Adapts AI reasoning to individual health contexts.
Sovereignty by Design: A Multi-Layered Security Architecture
World-class intelligence requires world-class security. Our architecture is built on a zero-trust model, ensuring that data sovereignty is not an afterthought but a core design principle. We protect data at every level, from the hardware up to the blockchain.
Trusted Compute: Zero-Exposure Analysis
All sensitive computations are performed within Trusted Execution Environments (TEEs). These are secure hardware enclaves that physically isolate data during analysis, ensuring host-proof confidentiality. Even we cannot access the raw data, only the verifiable results of the computation.
On-Chain Verifiability: The Blockchain Layer
Our blockchain technology serves as the system's immutable ledger. While no health data is stored directly on-chain, the blockchain provides:
- Verifiable Consent: User-driven data permissions are cryptographically signed and immutably stored as on-chain transactions.
- Data Provenance & Proof-of-Origin: Data purchasers can verify the origin, authenticity, and lineage of any dataset, ensuring its integrity from source to analysis.
- Auditable Security: All access rules and data interactions are governed by smart contracts, creating a permanent, publicly verifiable audit trail.
Premium Health & Medical Data: The Fuel for Discovery
The power of AI depends on the quality of its data.
LIFE Networks collaborates with hospitals, biomedical companies, and Medical AI Alliance to curate verified, multimodal biomedical datasets – fueling the world's first DeSci infrastructure for real, usable science.
Real-World & Biometric Data
- Body Composition: Fat, muscle, water, phase angle via DEXA-verified clinical accuracy.
- Vital Signs: Real-time ECG, HR, SpO2, NIBP, IPI & EWS risk scoring.
- Longitudinal & Wearable: Data from global fitness chains, smart fitness devices, and functional health supplement tracking.
- Predictive Health: Health checkup prediction data from over 1.5 million cases.
Clinical & Diagnostic Data
- Oncology: Global Phase 3 clinical trial data for liver, colon, and stomach cancers; multi-omics diagnostic datasets.
- Neurology: Brain MRI (DWI/PWI) & CT analysis data with quantitative stroke indicators and DICOM AI segmentation.
- Chronic Disease: Large-scale big data for diabetes and obesity with AI-based disease prediction models.
- General Clinical: EMR-linked monitoring logs, AED/CPR data, and clinical speech-to-text data.
Genomic & Molecular Data
- Molecular Diagnostics: PNA-based molecular diagnostic results and companion diagnostics (CDx) data.
- Drug Discovery: AI-driven drug discovery outputs and multi-omics research datasets.