The engine behind Legal Intelligence

Legal Intelligence adapts and grows with a firm because of the engine underneath it. One semantic model, one projection per firm, construction from within.

Legal Intelligence is the first product on this engine. If you are evaluating whether the engine can carry more of your firm's work, here is what sits underneath. The engine has three parts, and the rest of the page reads each on its own terms.

The third path

The trade most software forces

Static software

SaaS and traditional ERPs are broad but fixed. Each business uses a fraction of the product and works around the rest.

Free-form AI builders

Flexible, but unbounded. They will build whatever you ask, including software that does not work or does not fit the business.

Adaptive and self-constructive software

What Kacti AI builds. Software shaped to the business, kept inside a model of the domain so it stays valid.

Static systems make the business fit the software. Free-form builders make correctness the business's problem. Kacti AI is built around the business and kept inside the model.

How it works

How it works

The semantic model

The semantic model defines what can validly exist in a domain: its entities, relationships, constraints, building blocks, and the processes that connect them. It is the source of truth, readable by both people and the agent, and the boundary of what can be expressed.

Projections

Each deployment is a projection of the model: one valid, fitted slice expressed for how a single firm works. No firm carries the weight of the whole system; each runs the slice that fits its work.

Construction from within

An embedded AI builder sits inside the product. It learns the firm's requirements in conversation, then carries the full build cycle from vision through implementation: clarifying what is being built, modeling the work, designing the change, and writing the code that ships. Coding is one step. The build cycle stays inside the product, and each change is checked against the model before it goes live.

The load-bearing claim

Correct by construction

The platform is designed so the agent builds within the model and verifies each change against it through a disciplined build cycle, the same way a typechecker rejects code that does not match its types. Invalid software is unrepresentable by construction, not merely discouraged. Adaptation without giving up correctness.

Traditional software is built once for everyone. Free-form builders trust the model to stay correct on each prompt. Kacti AI builds within a model, so flexibility and correctness hold together.

Foundational technology

Foundational technology

The work under the engine spans three areas. Each is foundational, closer to what the engine runs on than to any single feature.

Modeling

How to define what can validly exist in a domain so software built on it stays inside its meaning. Entities, relationships, constraints, building blocks, and the processes that connect them, expressed in a form readable by people and by an embedded AI builder.

Construction

How an agent extends a running deployment from within, guided by the model, with each change checked against the model before it goes live. The build cycle stays inside the product, and the model bounds what construction can produce.

Runtime

What it takes to hold a model and its projection in a live system, and to keep them aligned as the projection changes. The runtime is where the model meets a running deployment; everything downstream depends on what it admits and what it refuses.

Bring your firm's work

If you are evaluating whether this engine can carry more of your firm's work, the conversation works best with a specific operation in mind.