Your app shipped in a weekend. We read it like it is going to production.
Axionic Readiness Review connects to your repository and your live URL, runs deterministic scanners and frontier-model analysis against a seven-pillar rubric, and returns an architect-reviewed report where every finding points to a line of code. The rubric is three decades of building and scaling real production systems, taught to a frontier model.
[D] deterministic scanners[L] model analysis, labelled as analysisRead-only repository access
Sample output
R1 Hardening CandidateSEC-004 [D] Critical
Evidence: netlify/functions/checkout.ts:41-58
The problem
It looks done.
Done and ready are not the same thing.
Modern tools ship a working app in an afternoon. The screens work, the demo lands, the deploy is green. What they do not show you is the delete that runs on the wrong key, the admin route with no auth check, the secret in the git history, the payment status the client is trusted to set.
These defects read as plausible code. Human review misses them because they look right. They are found when a real user, or an attacker, arrives. This is the gap between an app that demos and an app that can carry a business.
Why it is different
The moat is not the model. It is what we taught it.
Anyone can point a model at a repository. The signal is in the rubric and the review: three decades of shipping and scaling production systems, the failures we have seen manifest in the field, encoded into how the model is directed and how a human checks it. The result reads with the judgement of a team that has carried real systems to scale, applied to every line of your code. That is the part that is hard to copy.
Evidence, or it does not exist
Every finding carries an evidence pointer you can open: a file and line, a config key, an endpoint, a dependency. A claim without evidence is discarded before it reaches you.
Labelled for what it is
Deterministic findings are marked [D]. Model analysis is marked [L] and written as analysis, never as fact. You always know whether a scanner proved it or a model read it.
Signed off by an architect
A person who has carried systems to production reviews the draft, disputes what does not hold, and puts their name to what does. The score you see is the post-review score.
What you get
7 pillars, weighted, every finding tied to evidence
Security
25%Scored one to five against the rubric dimensions, with each finding tied to a file, config key, endpoint or dependency.
Scalability
12%Scored one to five against the rubric dimensions, with each finding tied to a file, config key, endpoint or dependency.
Maintainability
12%Scored one to five against the rubric dimensions, with each finding tied to a file, config key, endpoint or dependency.
Correctness
15%Scored one to five against the rubric dimensions, with each finding tied to a file, config key, endpoint or dependency.
Operability
12%Scored one to five against the rubric dimensions, with each finding tied to a file, config key, endpoint or dependency.
Data & Compliance
12%Scored one to five against the rubric dimensions, with each finding tied to a file, config key, endpoint or dependency.
AI / Agent Governance
12%Scored one to five against the rubric dimensions, with each finding tied to a file, config key, endpoint or dependency.
A business one-pager
Overall tier, the top risks in plain language, and a cost-to-harden range. Written for the person deciding, not just the person coding.
A findings register
Every finding with its severity, its pillar, its evidence pointer, and remediation you can act on. Exportable to your tracker.
A remediation roadmap
Three phases, safe to scale to enterprise, each with an effort range, so you know what to fix first and what it takes.
How it works
From request to reviewed report
Request your assessment
Tell us what you built and where it is headed. We set up your workspace and invite you in. Assessments are not self-serve: every one is scoped and reviewed by us.
Connect the app
Read-only access to the repository and your deployed URL. Nothing is written, nothing is changed. The token is encrypted and never logged.
Scan and analyze
Deterministic scanners prove the facts. Frontier-model passes read the code against the rubric, dimension by dimension, and confirm the risky parts against the live app. Every finding cites a line.
Reviewed report
A human architect confirms, challenges, or refines every serious finding before you see a word. You get a tiered report, a business one-pager, and a remediation roadmap.
Readiness tiers
Where an app can land
- R0Prototype
Demonstrates the idea. Treat as disposable blueprint. Rebuild for scale.
- R1Hardening Candidate
Salvageable core. Requires structured hardening before any real users or data.
- R2Conditionally Deployable
Deployable to a constrained internal audience with named risks accepted in writing.
- R3Production Ready
Ready for production with a live remediation backlog.
- R4Enterprise Grade
Meets enterprise bar including audit and compliance posture.
What it is worth
The coverage of a frontier model. The judgement of thirty years.
A frontier model reads your entire codebase against the rubric, then confirms the risky parts against the live app. Every file, every pillar, every finding tied to a line. No sampling, no skimming, no blind spot waved away.
Behind that rubric and the sign-off are three decades of building and scaling production systems. This is the read a senior architecture team gives, at a depth and speed a manual review cannot reach. It is set up, reviewed, and signed off by us, never a checkout button, because the value is in the judgement.
Frontier coverage, senior judgement.
- Every line of code read against the rubric
- Every finding tied to evidence you can open
- Signed off by an architect who has shipped at scale
The depth a senior team bills weeks for, delivered in days and ready to act on.
After the report
From knowing to fixing.
A readiness report tells you what to do. Axionic Agents is how a coordinated team of AI agents does it, connected to your tools, composed into workflows, executing under your review. The scan is where that conversation begins.
Readiness scan
-> architecture conversation
-> a workforce that ships the fixes
Who we are
The architecture layer between your vision and your code.
Axionic is a team of senior, Big Four caliber architects with three decades of building and scaling production systems. We do the work fast tools skip: turn strategy into a technical blueprint, then govern the build. This assessment is one of three ways we work with you, and often where the conversation starts.
- Diagnose
- this readiness scan
- Architect
- senior architecture and delivery governance, axionic.agency
- Execute
- Axionic Agents, an AI workforce, axag.ai
Find out what is under the hood, before your users do.
Read-only access, an architect-reviewed report, and a clear path to production. Tell us about your app and we will take it from there.
Request your assessment