HOW CODEINTENT® WORKS
See it in CodeIntent Studio
Modernization projects don’t stall because code can’t be generated. They stall because no one can confidently review and accept the result.
HOW THE EVIDENCE LAYER IS BUILT
01
Extract
Read the installed source and identify what it actually does at runtime, not just what the syntax suggests.
02
Define
Build a canonical, source-derived representation of that behavior, independent of the original language.
03
Generate
Produce the modernized target from the governed baseline, with every line linked back to the rule and source construct it came from.
04
Verify
After cutover, use the governed baseline to check every proposed change, from a developer or an AI tool, before it’s accepted. For every change, CodeIntent records a disposition, so reviewers can see what was accepted and what still needs a decision.
THE SIX DISPOSITIONS
Disposition
What it means
Verified
Demonstrated equivalent to source
Preserved
Behavior kept intact, traced to its construct
Allowed Change
Altered under a governed rule, not by accident
Net-New
No legacy source, governed anyway
Review Boundary
Ambiguity surfaced for human review, never guessed
Orphaned
Dead or unreachable source, explicitly dropped
Nothing is silently dropped, and where the source-derived understanding can’t determine an answer, it says so instead of guessing.
DETERMINISTIC, BY CONSTRUCTION
Same source, same rules, same output, every run. CodeIntent doesn’t generate a plausible answer—it computes the same answer every time, and every generated line carries a chain of evidence back to the source it came from.
Same source. Same rules. Same output.
The result is auditable because the source-derived baseline is repeatable by construction, not policy language wrapped around probabilistic output.
WHERE LLMS FIT
LLMs do
CodeIntent® does
Generate candidate code quickly
Supplies deterministic semantic context
Refactor obvious paths
Preserves source-to-target traceability
Propose architecture changes
Verifies preservation and change decisions
Power agents and copilots
Creates an audit trail of what changed and why
GOVERNANCE AFTER CUTOVER
Once a system is modernized, the same governed baseline governs what happens to it next. Proposed changes, whether from a developer or an AI coding tool, are checked against it before they’re accepted. This is live today via MCP.
A control layer that keeps working.
Modernization creates the baseline that remains the permanent source of truth for future review, governance, and AI-assisted development.
SEE IT AT WORK
Reading about it only goes so far. CodeIntent Studio is where you watch it applied to a real system.
Explore CodeIntent Studio →
HOLONIC
PRODUCT
COMPANY