NeoSyntropy

Deterministic control for AI workflows

Models interpret. Your application decides and executes. NeoSyntropy turns AI workflows into controlled graphs with application-owned schemas, tools, validation, routing, state transitions, and business policy.

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Focused role models

Model Responsibility
Runtime Structure Structured extraction into application-owned schemas
Runtime Route Valid workflow topology and candidate selection
Runtime Deterministic Reasoning Schema-constrained reasoning and declared tool calls
Runtime Stochastic Reasoning Open reasoning with controlled tool requests
Runtime Guard Evidence-based validation against supplied rules
Runtime Score Rubric-grounded scoring and measurement

One contract from data to inference

Workflow contract → diverse scenarios → teacher gold → schema and semantic validation → critic gate → frozen evaluation → role adapter

Every accepted sample preserves prompt version, source lineage, teacher provenance, validation checks, and a canonical content hash. Training artifacts and metrics are published only after evaluation against frozen test sets. Each model card links to its matching private, versioned pilot dataset for inspection.