I built a closed loop demo that uses IBM Quantum to train a model, Akida monitors, IBM Granite and vLLM report on it, and Z/OS settles the trades.

Several platforms become one. Four different cadences matched together. 

Symphony makes it possible to route each task to the right platform automatically. What that unlocks is a closed-loop architecture where quantum trains the model, a neuromorphic chip runs inference on every market tick, a GPU generates compliance narratives and a mainframe settles trades. Seeming disparate elements join together to form a single platform.

But the real question is: when does each tier fire? Not on a schedule, only when the market says so.

Quantum Training
The Parametrized Quantum Feature Map runs on historical market data, months or years of historical trading. In this demo, IBM Quantum transforms 14 classical features into 48 quantum-encoded features using a 16-qubit Heisenberg ansatz. IBM and HSBC demonstrated this approach on real production bond data yielding a 34% AUC improvement over classical features alone.

That model gets quantized and compiled to a binary deployed on a BrainChip's Akida neuromorphic chip. The advantage is encoded in the weights. No quantum hardware or platform needed for inference.

Neuromorphic Handles the Real-Time Volume
The Akida chip classifies every market tick in a portfolio. 622 microseconds per classification. Mere milliwatts or less. 99%+ of events produce no regime change. The chip consumes almost no power doing continuous monitoring.

But when the regime does change (low volatility to high or trending to mean-reverting) that detection fires in under a millisecond.

A market regime change triggers everything in parallel.

A regime change means the model was trained on data from the previous regime. It can be retrained on the new one. So Symphony fans out to all three downstream tiers simultaneously:

The PQFM service retrains the model on recent data. The vLLM service generates a compliance-grade risk narrative. The z/OS mainframe settles any resulting trades through NOSTREC COBOL in 280 milliseconds. Not the 8 hours a batch job would take.

No tier waits for another. When retraining finishes in seconds, the new model deploys to Akida atomically. The chip is now tuned to current market conditions and goes back to watching every tick.

The Closed Loop
Through Symphony, Akida's neuromorphic chip triggers its own retraining. IBM Quantum improves the model the chip runs. An IBM Granite model on vLLM explains it for compliance/regulatory reporting. Then, z/OS settles outstanding trades.

No tier sits idle. No tier does work that belongs to another. The model never drifts until someone notices. It adapts the moment market conditions change.

Symphony Manages the Complexity
All of these environments are managed as SOAM services through one orchestration layer. The right task goes to the right place automatically.

That's what a platform looks like when it closes the loop.