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  • BreezeAI

    BreezeAI

    AI engineering agents that know your whole application

Overview

BreezeAI is our AI-native software development platform. It extracts your application into a four-layer semantic model, functional intent, design, architecture and code, and grounds every engineering agent in the layer its task needs. Agents propose changes but BreezeAI also validates each one against the model before it lands, so delivery gets faster without giving up correctness. 

The Challenge

Coding assistants accelerate typing while the engineering judgment around them stays manual. Even assistants that index the whole repository see code without the intent, design decisions or runtime behavior behind it, so suggestions drift, and the drift surfaces as rework in review or as incidents in production. Engineers still spend the day re-explaining the system to the tool, task by task. The tipping point is scale: once assistant-written code carries a meaningful share of commits, ungoverned drift compounds faster than review catches it. 

What We Deliver

  • A living four-layer model. BreezeAI builds and maintains a model of your application across Functional (what it does and for whom), Design (how it looks and behaves), Architecture (how it is organized), and Code (what is built).

  • Parsed and custodian-verified layers. Code and architecture are parsed directly. The Functional layer is extracted by model and signed off by its named custodian before agents ground on it.

  • Broad language coverage. Parsers cover TypeScript, JavaScript, Python, Java, C#, Go, PHP, and more. Extracting a multimillion-line brownfield codebase takes weeks.

  • A fleet of engineering agents. Analysis agents traverse the graph and emit impact reports, generation agents produce code and specs under structural constraint, validation agents check every change against the model before merge, and sync agents keep the graph current.

  • An MCP integration hub. Connections to Jira and Azure DevOps, Git, CI/CD, and design tools make adoption incremental inside your existing toolchain.

  • Deployed in your environment. The graph runs in your environment, with pluggable model endpoints.

  • Grounded on SKG. SKG, Accion's semantic knowledge graph, generalizes the same ontology into the governed graph layer the wider platform set stands on.

How We Do It 

One loop across the lifecycle

By grounding agents in the model and validating every change against it, BreezeAI applies a single loop across coding, testing, documentation, brownfield change, and release.

Analysis in minutes, not days

Impact analysis that once took days of archaeology returns in minutes. 

Evidence with every output

Every agent output carries evidence of what it checked. 

How BreezeAI Works

model-1

Model

Extract and maintain the four-layer ontology of the application: functional intent, design, architecture and code.

ground

Ground

Give each agent the task-specific slice of the graph it needs, nothing more.

Validate

Validate

Check every proposed change before it lands: structural consistency with the graph, contract and interface agreement, and generated tests.

Accelerate

Accelerate

Apply the loop across the full lifecycle: coding, testing, documentation, modernization and release. 

What You Get 

A living four-layer model of your application 

Engineering agents grounded in that model 

Pre-merge validation with evidence 

Generated tests and documentation 

Intent-to-code traceability 

Incremental adoption inside your existing toolchain 

Proof Points

01

Enterprise product engagement

Generated 93.4% test coverage with no manual behavior-driven-development overhead. 

02

Enterprise product engagement

Cut the defect rate 23% against the same team's baseline before Semantic Engineering.

03

Brownfield estate

Returned impact analysis across a 1.6 million-line application graph in 8 minutes.

Why Accion

Semantic Engineering at the Core

Agents ground in a governed model of your whole application, never in a lone file. 

Tool-agnostic integration

Plugs into the Jira or Azure DevOps, Git and CI/CD you already run; adoption is incremental. 

Agents earn autonomy

 Every agent starts supervised and advances only on accumulated evidence; autonomy revokes automatically if reliability drops.

Validation before merge

Structural, contract and test gates emit evidence on every change. 

Whole-lifecycle reach

One model powers coding, testing, documentation, modernization and release. 

Constantly evolving

Battle-tested through years of commercial deployments, knowledge that transfers to you.

Relevant Links

See what BreezeAI finds in your code

BreezeAI turns a codebase into a four-layer graph and impact report, surfacing risk before work begins. Talk to our team to get started. 

Request for Services

FAQs

BreezeAI is Accion Labs' AI-native software development platform. It maintains a four-layer semantic model of your application and grounds engineering agents in it, validating every change against the model before merge.

Today's assistants can index a whole repository; what they index is code. BreezeAI grounds agents in a governed model that also carries functional intent, design and architecture, and validates output against that model before merge. The difference shows up in review load, defect rates and the size of task you can safely hand to an agent. 

One methodology, two jobs. BreezeAI runs continuous engineering on live applications, greenfield and brownfield. ASIMOV runs bounded legacy migrations. When a migration completes, ASIMOV's governed model carries over into the four-layer ontology BreezeAI works on; adopting BreezeAI afterward is optional. 

BreezeAI applies Semantic Engineering at engineering time, to build and change software. SPEX applies it at run time, to execute operational processes. Both stand on the same governed graph foundation.