Support by
Abel Open System -
The Leading Intelligent Intent Network driven by Causal Planning
Hierarchical Structure
The system features a three-tier design: modules, agents, and products. This structure ensures flexibility, efficiency, and scalability.
Collaborative Evolution
The Collaborative Evolution Framework continuously adapts and enhances the system, driving ongoing improvements.
Causal Planner
At the core of ABEL Agent OS, Causal Planner employs causal reasoning to manage tasks, optimize resource allocation, and automatically resolve issues.
ABEL Open System
Causal General Intelligence (CGI)
Causality is the Key
CGI, the next generation of AI paradigm, delivers causality-driven insights and learned representations beyond pattern matching.
By leveraging Abel's Causal Machine Learning (ML) and Causal Language Models (LLMs), CGI ensures the predicted tokens and actions are logically validated and aligned with grounding facts behind the scene.
Proof of Causal Flow (PoCF) powered by CausalCore
PoCF verifies actions based on their causal impact, providing fair rewards and incentive security. To enable PoCF, we designed Abel CausalCore, feature delivers decentralized applications for data & IP, L1/L2 protocols, and Web3 social interactions, offering a scalable, modular, and intelligent solution for advanced AI-powered blockchain services.
Causality-secured Incentivized ML
Abel pioneers causality-secured machine learning—where every model decision is rooted in provable cause-and-effect, eliminating bias and hallucinations with fair rewards to ensure incentive-secured runtime, on-chain. AI evolves through transparent collaboration, users profit from truth, and enterprises deploy models they can trust, not just tolerate
Fair
Ensures Fair, Incentive-secured Agentic execution through Proof of Causal Flow Consensus to bootstrap open and decentralized AGI.
Factual
Causal reasoning to empower every decision to be Reliable, Auditable and Explainable.
Powerful
Causality empowers New Knowledge Discovery with fewer data and high efficiency, models 10X faster and smarter coordination of Meshed Intent Network for 10x Complex tasks, continuously evolving with Web 3 data.
Decentralized
CausalCore - our onchain runtime for open, fair, and trustless execution of Causality-secured Incentivized ML.
Gain a Competitive Edge with Datascend
Ecosystem Synergy
dApp and API/RPC Access
Abel's dApp and API/RPC access offer a standardized, user-friendly interface, enabling developers and users to easily leverage CGI capabilities.
Personalized Causal Agents
Personalized Causal Agents are AI-driven entities that adapt to individual user needs through causal reasoning—understanding not just "what" happens, but why and "what-if".
Causality-secured Incentivized ML Protocols
These protocols integrate external data—real-world events, user interactions, and blockchain data—into the Causal ML/LLM layer, enhancing data quality and improving causal insights. Users control data and logic via blockchain-backed protocols, enabling trustless collaboration, where rewards are secured from security game design.
Causal Foundational Models
We are pioneering the next evolution of AI by embedding causal reasoning into the core of large-scale models—LLMs, video models, and multi-modal systems.
We Define Success as …
Blockchain Native
Openness, Sovereignty and Ownership with Decentralization
Fairness
Fair Attribution of Contribution
Fact Grounding
Underlying Causal Knowledge Identification
Discovery
Unknown Knowledge Discovery
Strong Intelligence
Task Complexity, Intelligence and Evolution Quality
Abel.Ai
Believe in yourself
Building the Machine of Causality