Architecture Overview
1. Vision: Automation & Intelligence, Under Your Guardrail
Managing and owning a market intellegence AI is a right for all citizens — not a perk for institutions.
The stack is designed so anyone can:
Spin up their own Decision Agent.
Bind it to their identity, their capital, and their rules.
Let it run 24/7 — autonomous finance, under your guardrail.
#Autonomy: Agents that can reason, route, and execute on your behalf.
#Guardrails: Explicit, programmable constraints around risk, budget, and jurisdiction.
#Ownership: You own the agent, its strategy, its data exhaust, and its economics.
2. A Four-Layer Decision Intelligence Stack
TradeOS provides a four-layer architecture that turns market intent → strategy → reasoning → execution → provenance into a closed, self-improving intelligence loop.
2.1 Architecture Overview
💡 1. Strategy Layer
Where market intent becomes machine-executable logic. TradeOS turns vibes, indicators, and strategy rules into tokenized strategy objects that models and agents can understand, reuse, and improve.
This is the system’s strategy sensemaking fabric.
🧠 2. Decision & Orchestration Layer
The autonomous decision engine. Small models + quant signals + guardrails run continuous evaluate → filter → act loops, generating safe, context-aware decisions 24/7.
This is the system’s real-time reasoning brain.
💳 3 Execution Layer (Payment Rails)
Where decisions become verifiable actions & trades. - TradeOS routes orders across CEX/DEX/brokers
- Fetch services, data from global vendors and trigger micropayment
#Stablecoin #zkTLS guardrails, #TEE-secured wallets, and PoD settlement. Execution becomes secure, trustless, and venue-agnostic.
🛡 4. Identity & Reputation Layer
The ownership & provenance core for the AI economy. Decentralized identity, and a performance-based reputation graph — give every strategy, agent, and vendor a verifiable on-chain presence, to anchor trust, authorship, and economic value flow.
Let AI becomes an accountable, rewardable economic actor.
3. Cross-Cutting Infra
To truly democratize AI-native finance, the 3 layers are wired together by three cross-cutting infrastructure:
AutoML for Citizens AutoML pipelines continuously search, tune, and deploy better signals, models, and agent policies on behalf of users — without requiring quant or ML expertise. Users choose their comfort level; the system experiments within those guardrails.
SLM-First Agent Intelligence Lightweight Small Language Models (SLMs) are embedded close to the edge (browser, phone, wallet), enabling low-latency, privacy-preserving reasoning for everyday users. Heavy models stay in the cloud; SLMs keep your “local brain” responsive and under your control.
AI-Native Payment Rail A programmable AI payment fabric connects agents, venues, and service providers:
Usage-based payments for data, models, and execution.
Revenue-sharing for strategy creators and signal providers.
Automatic settlement tied to Proof-of-Delivery (PoD) receipts.
This turns TradeOS from “just infra” into a civic-scale AI finance network — where anyone can plug in, participate, and get paid
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