Wavect is best when
- You know AI could help but have not mapped which processes are actually worth it.
- You do not yet have a year of clear AI work to keep a full-time hire busy.
- You want your existing team upskilled, not a single point of failure.
AI ENABLEMENT vs IN-HOUSE AI HIRE
Hiring an AI engineer is a twelve-month commitment, and a strong one is hard to find and harder to keep busy with the right work. AI Enablement gives you the industry, process, and AI engineering know-how as a package: workshops plus done-for-you setup on your own infrastructure. Past the point where you have a year of clear AI work and someone senior to direct it, hire. Before that, the wedge wins.
Book a thirty-minute call“We hired an ML engineer who was brilliant and bored. The problem was never the model. It was that nobody had mapped which processes were worth automating.”
VerdictThe practical split: If the bullets on the right describe you, hire. If the bullets on the left describe you, start with enablement and hire later.
Six dimensions where the two diverge.
Per engagement. A workshop, an audit, or a scoped setup. No tenure.
COMMITMENTTwelve-month commitment plus ramp, recruiting, and the cost of a wrong hire.
Industry, process, and AI engineering in one team, plus domain experts on call.
BREADTH OF KNOW-HOWOne person’s skill set. Strong on the model, thin on your process unless they happen to know it.
Workshops in days. A first automation live in weeks.
TIME TO VALUEMonths to hire, then onboarding before the first useful output.
Token, context, routing, and caching engineered in from day one.
COST DISCIPLINEDepends on the hire. Cost control is rarely the first thing a new engineer optimises.
A documented setup on your infrastructure, plus an upskilled team.
WHAT YOU OWNEverything, including the risk that the role is underused before product fit.
We say so and rule the process out. Less work for us.
WHEN AI IS THE WRONG TOOLA full-time AI hire is incentivised to find AI-shaped problems.
An in-house AI hire is the right answer to a specific situation: you have a year or more of AI work, a clear sense of which processes matter, and someone senior who can point the work. When that is true, full-time is cheaper and tighter than any outside team.
The trap is hiring into the gap before that is true. A single engineer, however good, brings AI engineering but not your process knowledge and not a network of domain experts. They will build what they are asked to build. If the wrong process gets picked, the salary buys a polished automation of a step that should not have been automated.
AI Enablement is built for the before. We bring industry and process know-how, the tooling, and the AI engineering in one team, map where automation actually pays off, and set it up on your own infrastructure with cost control and compliance designed in. Your team learns as we go, so a later hire walks into a working setup instead of a blank page.
Once the work is steady and the direction is settled, hire, and we will hand over cleanly. See how the service works .
If the bullets on the right describe you, hire. If the bullets on the left describe you, start with enablement and hire later.
Tell us what you are building. We will tell you straight which route fits, no pitch.
Book a thirty-minute call