The tutorial walks through the full process:
- Preprocessing pipeline in a sandbox with tokenization and embeddings
- Mesh-based neural cluster with proof-of-learning consensus
- Validation agents enforcing input gates, scope checks, and quality rules
- Dual-model comparison against TensorFlow.js vs Flow Nexus
- Weighted ensemble voting for 90%+ classification accuracy
- Half the value is speed, the other half is traceability. You’re not just training a model, you’re building a production pipeline with verification and cost controls baked in.
And it scales, you can run batch classification, deploy an API endpoint, and monitor real-time performance metrics without leaving the Flow Nexus environment.