Continuous Verification
Verification is a loop, not a one-time report
Reqode runs focused AI verification against the current, branch-aware product model and implementation context. When a verifier confirms a problem, Reqode records it as a Finding with evidence, severity and links to the affected artifacts.
The team can then correct code, specifications, unit mapping or architecture guidance and run the relevant verification again. Findings are the operational output of this loop—not a separate quality-management system.
Specification consistency
Check a requirements module for contradictions, gaps and inconsistencies across its requirements and related API, UI and data specifications.
Unit discovery
Classify source files into meaningful software units and update unit types, dependencies and links back to product specifications.
Guidelines compliance
Verify a software unit against the subsystem Code Manifest, its Unit Type rules and unit-specific implementation guidance.
Specs ↔ code alignment
Compare a software unit with its linked requirements, data entities, user interfaces and API operations to detect implementation drift.
From verification to a resolved Finding
Each stage preserves enough context for the team to understand what was checked, what failed and what needs to change.
Select or schedule the check
Run a verifier from the module, software unit or files being reviewed, or configure an automation rule for a project branch and subsystem.
Prepare focused context
Reqode assembles the applicable specifications, software units, files, dependencies and architecture guidance for the selected scope.
Run AI verification
The focused verifier analyzes its defined concern and returns a structured result rather than a general-purpose AI opinion.
Record confirmed Findings
Confirmed problems become branch-aware Findings connected to the exact requirements, data entities, user interfaces, API operations or software units involved.
Resolve and reverify
Fix the appropriate source of truth, rerun the check and let the new result update or solve the corresponding Finding.
See exactly why verification failed
A Finding preserves the verification evidence, affected subsystems and artifacts, severity, validity and proposed resolution options. It can be opened from the Findings browser or directly from an affected artifact.
Where a verifier provides an AI Analyst solution action, the user can create a reviewable AI Analyst draft with the Finding and its related artifacts already included as starting context.
Manage verification results in product context
Browse Findings created by verification, filter them by state, severity, type and validity, and inspect them through the artifact structure used for the verification scope.
Evidence and scope
Understand the verifier rule, affected branch and subsystems, linked artifacts, description and suggested solutions.
Finding lifecycle
Keep a Finding active, intentionally ignore it, mark it solved or return it to active work while preserving its verification context.
Current validity
Distinguish current results from outdated Findings so old verification evidence does not look like the current product state.
Findings are not general-purpose Issues
Findings preserve problems and evidence produced by AI verification.
Issues organize human-planned work such as tasks, defects, ideas and other reasons for change.
A team can investigate the verified problem through a Finding and create or link delivery work only when that workflow is needed.
Manual and automatic checks
Launch focused verification when reviewing a specific artifact or schedule supported checks for module consistency, unit discovery, guidelines compliance and specs-to-code alignment.
Turn every confirmed drift signal into a closed loop
Verify focused context, preserve evidence, correct the right source of truth and prove the result with the next check.