Insights · FAQ
AI consulting FAQ — the questions owners actually ask.
Straight answers to the questions we hear most from business owners weighing up AI — on cost, data safety, hiring, timelines and what happens when a project has already stalled. No jargon, no hard sell.
Questions
I'm not even sure what AI can do for my business. Should I still book a call?
Yes — that is exactly the kind of call we like. Most of the strongest AI opportunities we see start as a business problem, not a technical brief: a process that is slow, a backlog that never clears, knowledge that lives in one person's head. You do not need to arrive with an AI idea. On a 30-minute call we will ask how your business actually runs and where the friction is, then tell you honestly whether AI is worth exploring and where a sensible first step would be. If the honest answer is that AI is not your priority yet, we will say so. When there is something worth pursuing, the AI Readiness Diagnostic is the structured way to pin down exactly what to build first.
How is this different from hiring an AI engineer in-house?
Hiring internally is a real option, but it is slow and narrow. A single hire can take months to find and onboard, and one engineer rarely covers everything a production AI system needs — software, data, delivery and operations. Lumitec AI gives you a small senior team across those disciplines without having to assemble it yourself. We can move quickly on the first build, then support it, operate it, or hand it cleanly to your own people once it is stable. That last point matters: we are not trying to make ourselves permanent. If the right outcome is an in-house capability, we will help you get there rather than holding the knowledge hostage.
Will my data be safe?
Data handling is agreed at the start of every engagement, before anything is built. We work inside your existing systems, identity and permissions rather than around them — Microsoft 365, Google Workspace and the other platforms your teams already use — so access follows the controls you already trust. Storage, retention and data-residency requirements are defined up front and documented, and UK data residency is available where you need it. We design so that sensitive data is only used where it genuinely has to be. Security is not a feature we add at the end; it is part of how the system is shaped from the first week.
What if a model provider raises prices or quality drops?
This is a real risk and we design for it. Where it makes sense, systems are built so that workloads can be routed between different models or providers as cost, quality and capability change — rather than being welded to one vendor's pricing and roadmap. The architecture around the model usually matters more than the model itself: clear interfaces, good evaluations, and the ability to swap a component without rebuilding the system. We also keep an eye on the market for you as part of Managed AI Operations, so a price rise or a quality regression becomes a routine routing decision rather than an emergency.
Are you going to try to sell me something we don't need?
No, and the way we work is built to prevent it. The AI Readiness Diagnostic is a paid, fixed-fee engagement precisely so that we are not using it as a sales pitch for a build. Charging for the diagnosis keeps it honest: our job in that engagement is to tell you the truth about where AI is worth the investment and where it is not. If the right answer is to do nothing yet, to fix a process first, or to do a smaller piece of work than you expected, that is what we will recommend. You leave the Diagnostic with a plain-English report you keep, whether or not we ever work together again.
How fast can you start?
Diagnostics typically start within about two weeks of agreeing scope. Build timelines depend on the work itself — scope, the integrations involved, and how ready your data is — but we deliberately work in focused, two-week phases rather than disappearing for months before a big reveal. That means you see something real early and can steer it. Speed is never the only goal: a system shipped quickly but unsafely is not faster in any way that counts. We would rather set a realistic pace at the start and hold to it than promise a date we would have to cut corners to hit.
Can you fix an AI project that's already gone sideways?
Often, yes. Stalled-project rescue is one of the things we are asked for most. We start with an honest review: what was being attempted, where it broke down, and what — if anything — is worth keeping. Sometimes the foundations are sound and the project simply needs refocusing and a clear delivery plan. Sometimes the right call is to rebuild part of it properly, and occasionally the most useful advice is to stop. Whatever we find, you get a clear, plain-English route forward rather than a vague reassurance. The aim is to get you to a working, supportable system — or to a clean decision — not to keep an unhealthy project alive.
What's the smallest engagement you'll take?
Most clients start with the AI Readiness Diagnostic, a fixed-fee engagement sized to the business — that is usually the smallest sensible piece of work, and a genuinely useful one on its own. Build projects are scoped around the value at stake, the complexity, and how much integration is required; smaller production builds typically start in the tens of thousands. We are not the right fit for a quick throwaway prototype with no path to production — that is not what we do well. But if you have a real business problem and want it solved properly, the Diagnostic is a low-commitment way to find out what that would take.
Still have a question?
The fastest way to get a straight answer is a 30-minute call. Tell us what you are trying to improve, automate or scale, and we will tell you honestly what we would do.
Book a free 30-min call →