Proof-based release for AI outputs
Proof-based release for AI outputs
Our Technology
Our Technology
The control point between generation and release
Consistency Systems is a deterministic certification gate placed between AI generation and real-world action. Upstream models may propose a result. The gate releases only outputs that satisfy explicit, machine-checkable rules.
If correctness cannot be established, the system fails closed — and routes the output to a policy-defined Safe Handling Path.
- Retry under constrained reformulation
- Alternate solver execution
- Fallback generation with re-certification
- Sandboxed execution
- Human review or escalation
No silent errors.
No unchecked propagation.
Every outcome is explicit, governed, and enforceable.
What Deterministic Certification Actually Means
Deterministic certification is an explicit outcome contract: CERTIFIED or NOT CERTIFIED.
The same input under the same policy yields the same outcome classification.
All required obligations pass. The output is released with reproducible artifacts.
NOT CERTIFIED does not mean the candidate is wrong. It means correctness cannot be established under the current policy and certification envelope. The outcome is returned with explicit reason codes.
Common NOT CERTIFIED reasons:
- Malformed or ambiguous input — the request cannot be deterministically interpreted into a certifiable form.
- Failed obligations — one or more required checks did not hold (constraints, equivalence, structural validity, invariants).
- Non-certifiable under active policy — the request or candidate cannot be proven correct within the current deterministic certification envelope.
How Certification Operates
1. Candidate Generation
An upstream system proposes an answer or structured claim.
2. Canonicalization
Syntax and structure are normalized to eliminate ambiguity.
3. Deterministic Enforcement
- Symbolic equivalence
- Constraint satisfaction
- Structural validity
- Invariant preservation
- Step consistency
If obligations succeed → CERTIFIED.
If the request is outside current kernel or ruleset scope → NOT CERTIFIED.
If correctness cannot be established under deterministic constraints → NOT CERTIFIED.
If execution cannot complete due to operational limits or service conditions → NOT CERTIFIED.
Test deterministic certification in your own pipeline
Use Developer Access to validate real prompts, outputs, and fail-closed behavior with your workflow.
The control point between generation and release
Consistency Systems is a deterministic certification gate placed between AI generation and real-world action. Upstream models may propose a result. The gate releases only outputs that satisfy explicit, machine-checkable rules.
If correctness cannot be established, the system fails closed — and routes the output to a policy-defined Safe Handling Path.
- Retry under constrained reformulation
- Alternate solver execution
- Fallback generation with re-certification
- Sandboxed execution
- Human review or escalation
No silent errors.
No unchecked propagation.
Every outcome is explicit, governed, and enforceable.
What Deterministic Certification Actually Means
Deterministic certification is an explicit outcome contract: CERTIFIED or NOT CERTIFIED.
The same input under the same policy yields the same outcome classification.
All required obligations pass. The output is released with reproducible artifacts.
NOT CERTIFIED does not mean the candidate is wrong. It means correctness cannot be established under the current policy and certification envelope. The outcome is returned with explicit reason codes.
Common NOT CERTIFIED reasons:
- Malformed or ambiguous input — the request cannot be deterministically interpreted into a certifiable form.
- Failed obligations — one or more required checks did not hold (constraints, equivalence, structural validity, invariants).
- Non-certifiable under active policy — the request or candidate cannot be proven correct within the current deterministic certification envelope.
How Certification Operates
1. Candidate Generation
An upstream system proposes an answer or structured claim.
2. Canonicalization
Syntax and structure are normalized to eliminate ambiguity.
3. Deterministic Enforcement
- Symbolic equivalence
- Constraint satisfaction
- Structural validity
- Invariant preservation
- Step consistency
If obligations succeed → CERTIFIED.
If the request is outside current kernel or ruleset scope → NOT CERTIFIED.
If correctness cannot be established under deterministic constraints → NOT CERTIFIED.
If execution cannot complete due to operational limits or service conditions → NOT CERTIFIED.
Test deterministic certification in your own pipeline
Use Developer Access to validate real prompts, outputs, and fail-closed behavior with your workflow.
