An honest comparison
A demo and a production system are not the same build.
A large number of firms will build you an AI prototype quickly and cheaply. The difference shows up at the point where it has to run reliably against real data, and stay working after launch.
The Frame
Web and app development shops with an AI practice attached, typically strong at interface work and quick to produce something demonstrable. Depth in the parts that come after launch - evaluation, drift, retraining, inference cost - varies enormously between firms.
Built by engineers whose background is production ML systems. Evaluation, guardrails, monitoring and handover are part of the deliverable rather than a later phase.
The gap is rarely visible in the demo.It appears in month three, when the data drifts, the costs climb, and nobody can say whether the system is still working.
Time to production
There is no figure opposite ours. Programme lengths vary far too much to state as fact, and inventing one would fail the same test that kept every other statistic off this page.
Side-by-side
Honest in both directions
If you need something demonstrable for a pitch or a validation test, this is often the sensible purchase and we would say so.
Many are genuinely excellent at the surface layer, which is a real discipline and not one to dismiss.
Not everything needs production ML rigour. A thin wrapper over a model API sometimes really is the whole job.
Evaluation, drift, retraining and inference cost are where AI systems actually fail, and they arrive after the launch.
Ask directly how they measure whether a model is still working, and what happens when it stops.
A prototype built without production concerns often has to be rebuilt to survive real load and real data.
Our engineers have run models in production, where the interesting problems are the ones that appear after launch.
You get the harness that proves the system still works, not just the feature that demos well.
Documented for your team to own and extend.
If you genuinely only need something to demo next month, we are the wrong choice and a prototype shop is the right one.
Some AI features really are a thin wrapper over an API. Paying for production ML rigour there is waste.
We ship the interface that carries the system, but brand and product design craft is not what we compete on.
Keep comparing
A direct conversation about the problem, the metric, and whether we are the right shape for it. If another option on this page fits you better, we will say so.
Talk to us
