Architecture Glimpse

3-Layer Decision Intelligence Infrastructure

🌏 1) Open Intelligence Layer

Goal: Structure how AI agents discover, access, and process real-time signals.

Key Components:

• Unified Catalog & Signal Engine — A standardized schema for multi-source data: indicators, price feeds, technical patterns, models, APIs, and contextual metadata. Enables real-time discovery, versioning, and streaming access.

• Search & Recommendation System — Semantic search and graph-based discovery let agents or users find relevant signals, strategies, or components by intent, context, and performance.

• Orchestration Hub — Optimizes routing between data sources and analytic services based on latency, cost, and quality; powers dependable, low-friction decision pipelines.

🧩 This layer defines the “market sensemaking fabric” — where data becomes machine-legible and composable for agents.

⚙ 2) Decision Execution Layer

Goal: Power 24/7, autonomous decision flows through personalized AI agents.

Enables transactions to be executed, fulfilled, and paid out in a verifiable, secure & programmable manner:

• Vibe Coding Engine — Natural-language compiler (Ora Language) that translates user intent—indicators, context, trading style, and personalization—into executable decision graphs.

• Agent Runtime & Scheduler — Executes these decision graphs continuously, maintaining context and adapting to live signals; supports both real-time actions and simulated backtests.

• Adaptive Memory Core — Retains contextual states such as recent market patterns, user preferences, and past outcomes, enabling continuous learning and feedback loops.

• Guardrails & Verification — Every execution runs within user-defined risk, timing, and logic constraints; outputs are cryptographically logged for transparency.

⚡ Think of this as the “always-on execution brain” — your personalized decision engine, tuned to your logic and style.

🪪 3) Identity & Intelligence Layer

Goal: Make every Decision Agent and dataset traceable, ownable, and composable.

Key Components:

• DID Registry — Issues decentralized identifiers binding each agent, user, or data vendor to a verifiable on-chain identity.

• Reputation Graph — Aggregates agent performance, reliability, and peer validation into a dynamic trust score that informs discovery and access limits.

• Intelligence Provenance Ledger — Records lineage and versioning of each agent’s decision logic, enabling reproducibility and credit for original strategies.

🔍 This layer anchors transparency and ownership — every piece of intelligence, from model to decision, is verifiable.

From vibes to verified decisions — TradeOS turns personal strategy into autonomous intelligence.

🌐 Modular by Design

Each layer is interoperable and can operate independently or as a unified stack:

• Developers integrate through APIs or SDKs.

• Traders use Vibe Coding Studio to compose agents visually.

• Researchers connect custom models or datasets into the unified catalog.

🧩 Summary

Our infra provides the AI-native infrastructure for 24/7 personalized decision execution — where strategies are defined by your indicators, context, and style, not by preset platforms.

From vibes to verified decisions — TradeOS turns personal strategy into autonomous intelligence.