AI product consulting that ends in a decision
In short
What does AI product consulting involve?
AI product consulting is senior engineering judgement applied to a decision you have to make: whether an architecture will hold, whether a codebase is worth keeping, or whether an AI feature will work on your data. Onpolar delivers it as a written assessment with the evidence attached and, where it helps, the code that proves the point.
- Formats
- Review · audit · due diligence · fractional
- Shortest engagement
- One week, fixed scope
- You get
- A written assessment, not a deck
Updated
Example
One review, day by day
How a one-week architecture review runs.
- Day 1ScopeYour concern turned into a question that has an answer.
- Days 2–4ReadCode, documentation, incident history and dashboards.
- Days 4–7TestBenchmarks and a proof of concept wherever feasibility is the question.
- Day 8DecisionA written assessment, walked through live with your team.
What you get
Architecture review
Will the design hold as you grow, and what breaks first.
Code and security audit
Risks ranked by what an attacker or an outage would hit first.
Technical due diligence
What you are buying, and what it will really cost to own.
Fractional principal engineer
A senior engineer in your standups and pull requests, a set number of days a month.
How it works
- 01
Ask
A free 30-minute call turns a worry into a question with an answer.
- 02
Assess
We read the code and test the claims instead of interviewing about them.
- 03
Decide
A written answer you can take to your board or your team.
Compared
An engineering review vs a strategy consultancy
| Compared on | Engineering review | Strategy consultancy |
|---|---|---|
| Done by | The engineer who could build the fix | Analysts and slides |
| Based on | Your code and real numbers | Interviews and workshops |
| You get | A written assessment, often with code | A roadmap deck |
| Length | From one week, fixed scope | Open-ended |
Questions
How is this different from hiring a consultancy?
Onpolar reads the code. The deliverable is an assessment with evidence, often with a branch that shows the fix, written by the engineer who would also build it. There is no analyst layer between the person forming the opinion and the person who understands the system.
Who actually does the work?
The principal engineer. At Onpolar’s size that is arithmetic rather than a promise: you are not sold senior time and handed junior time.
Can you do technical due diligence on a company we are acquiring?
Yes. Code health, architecture risk, key-person dependency, licence and dependency exposure, and an honest read on whether the promised roadmap is achievable with the team being acquired, delivered as a report an investment committee can use.
Will you review AI-generated code?
Often. Prototypes from Cursor, Lovable, Bolt, v0 or Replit tend to share the same problems: no migrations, permissive access rules, secrets reachable from the browser, no indexes and no tests. The audit separates what is dangerous from what is merely untidy, so the hardening work is scoped rather than guessed.
Is there a smaller version for a single decision?
A 30-minute call is free and often enough. If the answer needs something read first, it becomes a scoped review, but plenty of questions are answered on the call, and Onpolar will not turn one into a project.