Large-Scale Simulations & Deep Research Flows
Execute long-running research tasks like large scale ecosystem simulations, iterative drug discovery workflows, and deep AI-driven literature reviews without worrying about infrastructure timeouts.
The Challenge
Scientific workloads and complex research flows often require tasks that execute over hours. A single drug discovery iteration might involve querying databases, running structural predictions, and evaluating results before planning the next step. Simulating an entire ecosystem involves large fan-out scale where thousands of entities interact.
Serverless architectures fail due to execution time limits. Custom monolithic runners lack the fault-tolerance to recover seamlessly if a single step fails halfway through a 12-hour job.
MirrorNeuron Capabilities
- Large Fan-out Scale: Spawn massive numbers of logical workers natively distributed across a BEAM cluster.
- Iterative Flow Control: Define multi-step graph bundles where agents interact, pass artifacts, and loop recursively.
- State Persistence: Redis-backed job state ensures your long-running computations survive process restarts and updates.
Featured Blueprints
Ecosystem Simulation
A massive scale simulation where numerous agents interact within a virtual environment. Demonstrates MirrorNeuron's ability to handle high-volume message passing and state updates efficiently over time.
View BlueprintDeep Research Flow
An orchestrated agent loop that systematically explores topics, aggregates findings, and self-corrects based on intermediate results without blocking the core orchestration engine.
View BlueprintWhy simplicity matters for research teams
Scientific and research workflows are already complex enough. Teams often need durable execution without signing up for a much larger workflow platform. MirrorNeuron is positioned for that lighter path.