ENTERPRISE & CLOUD

We don’t compete with your AI tools. We govern them.

Most enterprise teams already use LLM-based coding tools across legacy and new systems. CodeIntent® Studio works alongside those tools rather than replacing them. When a proposed change is routed through CodeIntent, your team gets a governed, auditable review before deciding whether to accept it into production. It fits into the tools and workflows you already use, rather than requiring another platform to adopt.

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IDE-BASED AI ASSISTANTS · IN-HOUSE LLMS · YOUR OWN AGENTS, GOVERNED THE SAME WAY, LIVE VIA MCP.

HOW GOVERNANCE ACTUALLY RUNS

How does CodeIntent govern AI-generated code changes?

Before CodeIntent can govern changes to a system, it needs a model of what that system actually does today. That's a one-time step. Everything after it, every proposal from a developer or an agent, is checked automatically against that model.

Establish baseline

CodeIntent builds a deterministic model of the system as it exists today.

Agent proposes change

A developer or an AI tool proposes a change through the tools you already use.

CodeIntent identifies affected intent/rules

The proposal is checked against the governing rules it touches.

Preservation/change verdict

CodeIntent determines whether the proposal preserves behavior or changes it.

Bounded review

Where the answer isn't clear-cut, a specific, finite decision is routed to a human.

Evidence record

The decision and its reasoning are recorded, so the next check, and the next auditor, has it.

LLMs propose. CodeIntent checks the proposal against the system model and governing rules. The review runs via MCP from the tools your developers already use.

ESTABLISHING THE BASELINE

Line-for-line, or improved architecture. Your call.

Carry the system forward as it runs today.

For teams whose mandate is to get off an aging runtime without changing what the system does.

Modernize and improve in the same pass.

For teams who want a better architecture, not a line-for-line copy. New capability is added and tracked as net-new.

AT SCALE

91.3% pass rate under 10K lines. 15.3% above 50K.

RepoMod-Bench reports an average pass rate of 91.3% below 10K LOC versus 15.3% above 50K LOC across four agent configurations; a 76-point gap. The bigger and more interconnected your systems, the more that gap costs you. CodeIntent doesn’t replace the agent; it checks what the agent proposes before it reaches production.

WHERE LLMS FIT

LLMs propose. Holonic verifies.

LLMS DO

Generate candidate code quickly

Refactor obvious paths

Propose architecture changes

Power agents and copilots

CODEINTENT DOES

Supplies deterministic semantic context

Preserves source-to-target traceability

Verifies preservation and change decisions

Creates an audit trail of what changed and why

FITS INTO YOUR STACK

Ingest. Baseline. Validate. Govern.

If your codebase is already in reasonable shape, Ingest, Modernize, and Validate move fast. Govern is where CodeIntent earns its place: every change your developers and AI agents make afterward is checked against the same baseline, before it's accepted by your team into production.

See the full model →

· See it in CodeIntent Studio →

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See the governed check run on a codebase built to mirror your stack.

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HOLONIC

The deterministic evidence layer underneath legacy modernization and the agentic enterprise.

PRODUCT

CodeIntent® Studio

How CodeIntent® Works

COMPANY

CodeIntent® is a registered trademark of Holonic Technologies.