Many companies hit the same crossroads. Someone inside has proposed an AI project, or a vendor has pitched an attractive offer — and nobody in-house can judge whether it’s a good idea, whether the price is fair, or whether the proposed technology is the right one. Independent AI project advisory is built for exactly that moment.
Advisory isn’t full implementation. We don’t run the project; we help you evaluate it, make the right calls, and avoid the most expensive mistakes before you commit resources. It’s the difference between the lawyer who reviews the contract and the contractor who does the build.
What is AI project advisory, and when do you need it?
AI project advisory is independent support for companies that already have an AI project underway or under evaluation and need a second technical and strategic opinion with no conflict of interest.
You need it when you’re weighing a technology vendor’s proposal and have no one in-house to validate it. When an AI project is in trouble and you need to know what went wrong and whether it can be saved. When your technical team has proposed an architecture and you want it checked before you approve the budget. Or when you’ve spent months investing in AI without results and can’t tell whether the problem is technical, data, management, or miscalibrated expectations.
In every one of these cases, having someone with 25 years at global multinationals leading data and AI — with nothing to sell — is worth more than any generic implementation report.
Why independent AI advice pays off
- Objective, unbiased evaluation: we have no commercial ties to any vendor, so the analysis is purely technical and strategic, built around your interests.
- Early warning: experience lets us spot red flags in a proposal or project before they turn into sunk costs.
- Real savings from mistakes avoided: advisory always costs a fraction of a poorly scoped project you have to scrap six months in.
- Internal credibility for decisions: outside validation makes it easier to get projects approved by management or the board — and to justify saying no.
- Built-in team training: during the engagement, your team learns to evaluate AI projects on its own for future decisions.
How we work: the maturity assessment
Advisory starts with the first phase of DALIA — Diagnosis — and stays there as long as it takes. Strategy sets the course and steers it all the way to scale-up; advisory answers an earlier question: where does this company really stand, and is what’s on the table feasible?
Technology maturity. What’s in place and in what shape: systems, integrations, architecture, vendor dependence, and accumulated technical debt. Without this foundation, any AI initiative is built on sand.
Analytics maturity. What gets measured today, how well, and who uses it to make decisions. We review the real state of the data — availability, traceability, governance — and the gap between what the company thinks it knows and what its data can support.
Organizational maturity. Team skills, who owns which data, and how much executive sponsorship is available. Most projects that fail don’t fail because of the technology.
Feasibility of what’s on the table. If there’s already a proposal — from a vendor or your own team — we audit it on its own terms: approach, technology, timelines, costs, and risks with estimated likelihood and impact. We present and defend our findings to the decision-makers, with alternatives wherever the approach falls short.
Follow-up. If the project goes ahead, we run periodic reviews to make sure it stays on track. Preventing drift costs far less than correcting it.
Common use cases
The situations where companies most often bring us in: evaluating proposals for process automation systems, validating data architectures before a cloud migration, reviewing chatbot or virtual assistant projects that aren’t delivering, and analyzing contracts with AI platform vendors that include exclusivity clauses or proprietary formats that create long-term lock-in.
Frequently asked questions
Does advisory mean AIRES will run the project afterward? Not necessarily. Advisory is a standalone service. If, after the review, you decide to go ahead with the original vendor, another one, or your own team, that’s your call. Our goal is for you to make that decision with the best information possible — not to create work for ourselves.
How long does an advisory engagement take? We agree on scope and timeline before we start, based on the project’s complexity and the documentation available.
Can you advise remotely? Yes. Most of the work involves reviewing documentation and video sessions. For large projects with an industrial component, a site visit can help, but in most cases it isn’t essential.
What do you need from us to get started? The proposal or project documentation, basic information about the data available, and access to the person who owns the project internally. With that, we can do an initial review and tell you whether it’s worth going deeper.
Get advice on your AI project
If you have an AI project under evaluation or in trouble and want an independent opinion, the first step is a 15-minute call to walk us through it. Free of charge.
Email us at info@airesstudio.ai or book a call with our team.