AI-readiness assessment
Which of your applications are ready for AI, and which are blocking it?
A scored review of your legacy applications against 15 checks: runtime, APIs, tests and data access. You get a ranked list and the fixes in order.
The short answer
An AI readiness assessment for legacy applications checks whether each system can support AI features and agents: current runtime, clean APIs, test coverage and reachable data. Ace8 scores each application against 15 checks and returns a ranked list with the fixes needed, in order of effort.
Why it matters
Why do legacy applications block AI?
AI features and agents need to call your systems and read your data. An application on an unsupported runtime, with no API and no tests, is hard to change safely and hard to connect to. The model is rarely the limit. The surrounding application usually is.
That is why Ace8 frames modernization as the way to become AI-ready. The same work that removes an end-of-life server also gives an agent something it can call.
The 15 checks
What do we check?
Each check is scored, and each application gets a total and a short list of the blockers. We keep the checks about applications, not about AI strategy.
| Area | Checks | What a fail looks like |
|---|---|---|
| Runtime | Java version supported; framework version supported; build reproducible | Java 8 with an out-of-support framework, or a build only one person can run |
| APIs | Documented interface; stable contract; authentication a service can use | Functions reachable only through a UI or a shared database |
| Tests | Unit and integration coverage; tests run automatically in CI | No tests, so no change can be verified |
| Data access | Data reachable by API or query; known owner; quality known | Data locked in an app server session or an undocumented schema |
| Operations | Logging and metrics; deploy with rollback | Manual deploys with a change window |
| Security and compliance | Open CVEs and secrets handling; audit trail for data access | Credentials in config files, no record of who read what |
Deliverables
What do you receive?
- A readiness score for each application, with the check-level detail behind it.
- A ranked list: ready now, ready after small fixes, and blocked by a runtime or architecture issue.
- The fix list in order, with effort ranges. Most start with a Java or framework upgrade; see Java upgrade.
- A short list of where an AI feature could safely use existing data and APIs now.
- A fixed price for the first fix phase, if you want it.
Process
How does it run?
We ask for read access to repositories and build files, a short interview with an engineer per application, and the list of applications you care about. We measure test coverage and open CVEs ourselves. A typical review covers a handful to a few dozen applications; the effort scales with the count, which is why we agree scope before we quote a price.
This is a lighter, AI-angled version of the full modernization assessment. If you want the target platform, licence baseline and phased roadmap, take that one instead; the readiness score is part of it.
Limits
What this assessment does not do
- It does not pick an AI model or vendor for you.
- It does not review your data governance or AI policy.
- It does not guarantee an AI feature will work; it tells you what stands in the way.
- It does not change any code. Fixes are a later phase.
After
What happens after the score?
The usual first fixes are a runtime upgrade and tests, which give an agent a safe target to work against. The upgrade work follows our method: test first, change in small steps, measure before and after. Ace8 is the AI-assisted application modernization practice of AceMQ, and AceMQ supports the stack after go-live.
A review of whether your systems can support AI features. Ours focuses on legacy applications: runtime, APIs, tests and data access.
General reviews cover strategy, skills and governance. This one covers the applications themselves, which is where legacy estates usually get stuck.
It depends on the number of applications. We set scope first, then give a fixed price and timeline.
No. We need repositories, build files and engineer time. We do not need production access.
It is a narrower, AI-focused cut. The modernization assessment includes the readiness score along with target platform, baseline and roadmap.
Know the cost before anything moves.
A fixed-price assessment gives you the inventory, the risk score and a phased plan. Scope and cost are fixed before the migration starts.
Book a Fixed-Price AssessmentGet in touch
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Tell us what you run today. An engineer, not a sales script, replies within one business day.