The Stack Behind Agentic Intelligence

From foundation models to autonomous execution — a vertically integrated AI stack built for production, not presentations.

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
↓
RAG Layer Real-time retrieval, market data, fundamentals, sentiment
↓
Memory Layer Real-time state, persistent ledger, agent context
↓
Tools Layer API integrations, exchange connectors, data enrichment
↓
Agents Layer Specialized agents with typed events, consensus voting
↓
Execution Layer Autonomous order routing, risk gates, portfolio management

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
  • Signal quality scoring and deliberation
  • Agent weight adaptation via learning loops

Production Infrastructure

Not a notebook. Not a demo. Containerized services with event streaming, persistent storage, and managed engines running 24/7.

  • Container orchestration
  • Event stream sourcing
  • 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

What This Stack Actually Powers

Every layer above exists in production, serving real users. Here's what it runs.

QuorumTrade — Trading Intelligence

18 trading agents across 9 pipeline layers. Typed event bus, synchronous dispatch within a 5-second cycle, async Redis-backed replay for backtesting. Multi-agent consensus decides every trade.

How it works →

Votriz — Brand Intelligence

25 AI agents across 8 divisions. Multi-tenant FastAPI + ARQ worker, encrypted credential vault, Remotion render farm, LLM tier routing (Ollama → Claude → OpenAI). Content publishes only after human approval.

How it works →

MCPAI — The Framework

The same orchestration layer underneath every product: typed events, role-based tool access, event replay, and stateful agent memory. Not a library you install — the substrate every Fortunato product is built on.

Early access →

Interested in the technology?

We're looking for technical partners and collaborators who share our vision of AI that executes.