Technology — Fortunato AI

Architecture

Full-Stack AI Pipeline

Each layer builds on the previous, transforming raw data into autonomous action.

LLM Layer GPT-4, Claude, domain fine-tunes — reasoning foundation

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RAG Layer Real-time retrieval, market data, fundamentals, sentiment

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Memory Layer Redis state, PostgreSQL ledger, persistent agent context

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Tools Layer API integrations, exchange connectors, data enrichment

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Agents Layer 18 specialized agents with typed events, consensus voting

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Execution Layer Autonomous order routing, risk gates, portfolio management

Capabilities

Four Pillars of Our Platform

MCPAI Framework

Our proprietary multi-context, multi-persona AI framework. Agents maintain separate contexts, role definitions, and tool access — coordinated through typed event buses.

Typed event-driven communication
Synchronous dispatch, async logging
Role-based tool access control
Event replay for debugging and backtesting

Agentic Frameworks

Multi-agent systems where agents deliberate, vote, and reach consensus before acting. No single-model decision-making — every signal is stress-tested by specialized agents.

Consensus-based decision making
Regime-aware strategy selection
Trade Quality Score (TQS) deliberation
Agent weight adaptation via learning loops

Production Infrastructure

Not a notebook. Not a demo. Docker-orchestrated services with Redis event streams, PostgreSQL persistence, and launchd-managed engines running 24/7.

Docker Compose orchestration
Redis Streams event sourcing
PostgreSQL append-only ledger
CI/CD with import validation and sim cycles

Domain Expertise

Deep vertical integration. Our agents are not generic — they encode domain-specific knowledge about market regimes, risk management, growth funnels, and operational workflows.

Regime detection (trend, range, volatile, crash)
Multi-asset coverage (crypto + equities)
SaaS growth pipeline modeling
Food service demand forecasting