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.