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AI Apps

What an AI App Actually Is, and What It Is Not

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Three things, one label

A chatbot answers questions in a conversation. An AI feature adds model capability to software that already does a job. An AI app is an application whose central function would not exist without the model.

The distinction matters because the cost differs by a factor of five, and because most ideas are the middle one.

Which is yours?

  1. If it would still be useful with the AI removed, it is an app with an AI feature
  2. If removing the AI leaves nothing, it is an AI app
  3. If the whole interaction is a conversation, it is a chatbot
“We want an AI app that helps our team find information in our documents” is a retrieval feature inside an internal tool. Building it as a standalone app usually costs more and gets used less, because people do not visit a second destination.

What a real AI app looks like

  • A document processing application where extraction is the product
  • A matching platform where semantic similarity is the whole value
  • A drafting tool where generation is the core workflow
  • A monitoring system where classification of unstructured input is the job

In each case, remove the model and there is no product left.

What every AI app needs beyond the model

The model is a small part of the build. What surrounds it is most of the work: an evaluation set, a review and correction interface, failure handling, cost controls, monitoring for quality drift, and an audit trail.

Budget roughly as much for that as for the feature itself. Skipping it produces a demonstration rather than a product.

Cost and time

Typical costTimeline
AI feature inside existing software£15,000–£40,0008–16 weeks
Standalone AI app, one workflow, one role£40,000–£90,0003–5 months
Multi-role AI platform with billing£90,000–£200,0005–9 months

Frequently asked questions

Do we need to train our own model?

Almost certainly not. The overwhelming majority of business AI is built on hosted models with good retrieval and prompting. Training is justified in narrow circumstances and is rarely one of them.

Can we start with a feature and grow into an app?

That is usually the right sequence. Prove the capability inside something people already use, then build the standalone version if the demand is real.

What if the model gets better and makes our app pointless?

Build the workflow, the data and the interface as the product, with the model abstracted behind a thin interface. Then a better model improves your app rather than replacing it.

How do we know if the idea is viable?

Test the approach on fifty real cases with known correct answers before commissioning anything. That costs days and settles arguments that would otherwise run for months.

Keep reading

Not sure whether yours is an app or a feature?

Describe what users would do in it. We will tell you which category it falls into and what that means for budget.

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