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Finance and market operations

On-edge financial workflows and market simulations

Build agents that monitor market signals, test risk scenarios, and summarize exposure close to private data feeds and internal systems, with cloud deployment still available when scale calls for it.

Fast proof

Run a market-risk blueprint before building a workflow platform.

MirrorNeuron keeps the finance workflow close to normal code: install, run a blueprint, inspect the trace, then swap mock feeds for your adapters and controls.

>_Run finance blueprint
$ mn blueprint run finance_liquidity_microstructure_radar

Private feeds

Run analysis close to sensitive market data and internal systems.

Durable monitors

Keep risk loops alive with retries, checkpoints, and recovery.

Cloud-ready path

Move the same workflow shape to larger deployments when needed.

The challenge

Financial AI work rarely fits a one-shot agent script.

Market data feeds, risk monitors, and simulation loops often run for hours or days. Teams need durable execution near controlled systems without committing every early workflow to heavyweight orchestration.

Long-running execution

Agents can keep processing ticks, events, or review cycles without turning every step into a platform project.

Bounded runtime control

Executor leases and explicit workflow stages keep continuous work observable and resource-aware.

Recoverable decisions

Persisted state, replayable events, and checkpoints help teams recover from failed tools or restarted workers.

Featured blueprints

Start from concrete finance workflows.

Why teams choose MirrorNeuron here

Financial AI workflows often need the durability of a workflow engine, but teams still want a simple developer experience and data-local execution. MirrorNeuron keeps the runtime on-edge first while preserving the recovery story that long-running market workloads need.