What is ZeroTrain?
ZeroTrain is a deterministic, symbolic AI engine designed to execute
knowledge, semantics, and decision intent in a structured, auditable, and repeatable form.
It looks like AI—intentionally so—but it operates fundamentally differently.
- ZeroTrain is not a database query engine
- ZeroTrain is not probabilistic machine learning
- ZeroTrain is not an LLM wrapper, prompt system, or generative AI
- ZeroTrain is not trained on your data
- ZeroTrain is a deterministic decision engine
- ZeroTrain is symbolic, inspectable, and auditable by design
- ZeroTrain is built to execute knowledge and inference intent
- ZeroTrain is training-free by architecture
Why ZeroTrain Exists
Modern systems need a reliable way to turn structured information into deterministic decisions. ZeroTrain exists to:
- Execute defined business knowledge without training cycles
- Remove ambiguity from automated decisions
- Provide traceable, inspectable inference
- Eliminate probabilistic drift in critical workflows
What Makes ZeroTrain Different
- Deterministic: The same inputs always produce the same result.
- Symbolic: Decisions are based on defined logic—not statistical guesswork.
- Transparent: Every action can be traced back to its rule or condition.
- Deployment-ready: Runs in-memory, in the cloud, or exported (ONNX-compatible).
- Training-free: No model fitting. No retraining cycles. No data drift.
How ZeroTrain Works
ZeroTrain evaluates structured inputs against defined knowledge models to produce:
- Deterministic actions
- Confidence scores
- Execution logic trace
It operates through dynamic inference across defined features and conditions — without statistical estimation.
Who ZeroTrain Is For
ZeroTrain is built for engineers, architects, and decision designers who require:
- Deterministic automation
- Compliance-ready AI logic
- Auditable decision systems
- Explicit control over inference behavior