Technology

Deterministic verification.Software-defined controls for probabilistic AI.

Language models produce what is likely. Deterministic controls evaluate explicit conditions the same way every time. Codira puts the second around the first, so what was produced is kept distinct from what was checked.

Draft · verification

A plausible result and a requirement that has been met are not the same thing. A draft can read perfectly and contain a figure that appears in no source; a code change can look right and reference a function that does not exist. Neither problem is reliably caught by asking the model that produced it.

Codira's verification layer evaluates AI output against requirements that can be stated exactly: structures, constraints, policies and acceptance criteria. When a condition fails, the work is flagged, blocked or sent back, and the result of every check is recorded so a reviewer can see what was verified and what was not.

What verification covers.Conditions that either hold or don't.

Rule-Based Validation

Explicit rules evaluate output, with the same result for the same input every time.

Execution Constraints

Limits on what a workflow may do, enforced in code rather than requested in a prompt.

Policy Enforcement

Actions a model may recommend but never take, held back regardless of its output.

Output Validation

Structured results are checked against their expected shape before they are used.

Approval Gates

Work cannot advance past a gate while a defined issue remains open.

Traceability

Claims carry their provenance, so a statement can be followed back to its source.

Error Detection

Specific failures, such as unsupported figures or missing references, are named precisely.

Workflow Consistency

Checks run at the same points in every run, not when someone remembers to look.

Requirements

Verification is against what was asked for and defined, not against a model's own view.

Choosing the mechanism.Some requirements are rules. Some are judgment.

A quotation matching its source can be checked by code. Whether an argument is persuasive cannot. Good verification architecture knows the difference and applies the right mechanism to each.

Codira uses rules where requirements can be stated exactly, and routes the rest to professional review, so neither is asked to do the other's job.

AI where judgment and language help. Rules where accuracy is required.

Requirements · how each is evaluated

What it does not do.A passed check is not a guarantee.

Verification establishes that defined conditions hold. It is honest about what that does and does not mean.

  • A rule confirms a condition, such as a figure having a source; it does not prove the source is right.

  • Requirements that depend on interpretation or expertise are left to people, not forced into rules.

  • Verification reduces and exposes errors. It does not eliminate every possibility of one.

The rest of the architecture.Explore the other capabilities.

Predictable controlsaround probabilistic intelligence.

Deterministic verification gives professional AI work something it otherwise lacks: a record of what was checked, by what rule, with what result.