Runtime Guarantees
Quantlix enforces contracts, policies, and budget controls at the execution boundary of your AI system.
Strict by default. No silent behavior.
What We Mean by "Guarantee"
A runtime guarantee means:
Before a request reaches your model, it must pass structured enforcement.
Quantlix evaluates:
- • Structural validity
- • Feature alignment
- • Behavioral policies
- • Resource constraints
If any rule fails, execution is blocked or downgraded according to policy.
No implicit coercion.
No hidden retries.
No silent drift.
Runtime Enforcement Flow
Every request is enforced before execution.
Incoming Request
Schema Enforcement
Contract v1.2
Feature Contract
Contract v1.2
Policy Engine
Policy v3.0
Budget Enforcement
Budget v1.1
Enforcement Decision
Blocked
→ Decision Log
Execution
→ Decision Log
Decision Log
- ·Contract version
- ·Policy version
- ·Enforcement outcome
- ·Timestamp
- ·Violation codes
Incoming Request
Schema Enforcement
Contract v1.2
Feature Contract
Contract v1.2
Policy Engine
Policy v3.0
Budget Enforcement
Budget v1.1
Enforcement Decision
Blocked · Compliant
Blocked
Execution
Decision Log
- · Contract version
- · Policy version
- · Enforcement outcome
- · Timestamp
- · Violation codes
Incoming Request
Schema Enforcement
Contract v1.2
Feature Contract
Contract v1.2
Policy Engine
Policy v3.0
Budget Enforcement
Budget v1.1
Enforcement Decision
Blocked · Compliant → Execution
Blocked
Execution
Decision Log
- · Contract version
- · Policy version
- · Enforcement outcome
- · Timestamp
- · Violation codes
Enforcement Layers
Schema Enforcement
Purpose: Ensure request structure matches expected contract.
Guarantees
- • Required fields present
- • Types strictly validated
- • No unexpected properties (if strict)
- • Versioned schema enforcement
Failure behavior
- • Request blocked (400)
- • Structured violation code emitted
- • Event logged
Feature Contract Enforcement
Purpose: Prevent training/inference drift.
Guarantees
- • Required features present
- • Data types validated
- • Feature ordering controlled
- • Unknown features rejected (configurable)
Failure behavior
- • Canonicalization or rejection
- • Violation logged
- • Drift prevented before execution
Policy Engine
Purpose: Govern runtime behavior.
Capabilities
- • Retry limits
- • Rate limits
- • Guardrail enforcement
- • Custom validation rules
- • Severity levels
Policy modes: Enforce | Warn | Shadow
Every decision is versioned.
Budget Enforcement
Purpose: Control resource exposure.
Capabilities
- • Compute ceilings
- • Request ceilings
- • Retry amplification limits
- • Per-deployment quotas
Actions: Block | Throttle | Downgrade | Alert
Budget enforcement happens before execution completes.
Audit & Decision Logging
Purpose: Make runtime behavior explicit.
Every request produces
- • Policy decision
- • Violation codes
- • Contract version
- • Policy version
- • Enforcement timestamp
Exportable. Queryable. Deterministic.
Enforcement Modes
Enforce
Violations block execution.
Warn
Execution allowed but logged.
Shadow
Evaluated but not enforced.
Use cases: Enforce for production. Warn during rollout. Shadow for policy testing.
What Quantlix Does Not Do
- •It does not replace your compute provider.
- •It does not modify model weights.
- •It does not rewrite your business logic.
- •It does not silently coerce data.
It governs execution.
Guarantee Matrix
| Layer | Strict by Default | Versioned | Logged | Configurable |
|---|---|---|---|---|
| Schema | ✓ | ✓ | ✓ | ✓ |
| Feature Contract | ✓ | ✓ | ✓ | ✓ |
| Policy Engine | ✓ | ✓ | ✓ | ✓ |
| Budget | ✓ | ✓ | ✓ | ✓ |
Determinism at Runtime
AI systems become unpredictable as they scale.
Runtime enforcement restores determinism.
Quantlix ensures every request either complies — or fails explicitly.