How do I start building an AI-powered product?

Start with a clear business problem — not the technology. Define the outcome you want (e.g., reduce defects by 30%, automate customer triage), assess your data readiness, and scope a focused pilot. The best AI products start narrow: one workflow, one user type, one metric. Prove value with a proof-of-concept before scaling.

How much does it cost to build an AI product?

An AI proof-of-concept costs $30,000–$75,000. A production-ready AI product with custom models, integrations, and monitoring costs $75,000–$300,000+. The largest cost driver is data engineering (cleaning, labelling, pipeline building), which accounts for 60–80% of most AI project timelines. Starting with pre-trained models or transfer learning can significantly reduce costs.

What data do I need to build an AI product?

You need relevant, labelled data — typically hundreds to thousands of examples for supervised learning. For computer vision, that means annotated images. For NLP, domain-specific text. If you don't have enough data, options include transfer learning (adapting pre-trained models), synthetic data generation, or starting with rule-based systems while you collect real data.

How long does it take to build an AI product from scratch?

A proof-of-concept takes 4–8 weeks. A production-ready AI product takes 3–9 months. Timeline depends on data quality, model complexity, and integration requirements. Projects with clean, labelled data and a clear use case ship significantly faster. We recommend a phased approach: pilot in 6–8 weeks, iterate to production over 3–6 months.

Should I use off-the-shelf AI or build custom models?

Use off-the-shelf AI (OpenAI API, Google Cloud AI, AWS SageMaker) when the use case is generic (summarisation, basic classification, chatbots) and accuracy requirements are moderate. Build custom models when your use case is domain-specific, you need high accuracy, or you have proprietary data that gives a competitive advantage. Many successful AI products use a hybrid — off-the-shelf for common tasks, custom for the core differentiator.

What industries benefit most from AI-powered products?

Industries with large datasets and repetitive processes see the highest ROI: manufacturing (defect detection, predictive maintenance), healthcare (diagnostic imaging, patient triage), financial services (fraud detection, risk scoring), retail (personalisation, demand forecasting), and logistics (route optimisation, inventory planning). McKinsey estimates AI could generate $2.6–$4.4 trillion in annual value globally.

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How to Build an AI-Powered Product

Building an AI-powered product is less about the latest model and more about nailing the problem, the data, and the user experience. We've built AI into products across manufacturing, healthcare, and fintech. Here's how we think about it.

Start with the problem, not the tech

The best AI products solve a clear problem: detect defects, automate screening, predict churn, or personalise content. Start by defining the outcome you want and the data you have (or can get). Then figure out whether AI is the right lever—sometimes rules or simpler automation are enough.

Scope the first version tightly. One workflow, one metric, one user type. Prove value before you expand. We've seen too many projects stall because they tried to 'add AI everywhere' in v1.

Data, models, and deployment

You need enough quality data to train or fine-tune. If you don't have it, consider starting with an off-the-shelf model or a hybrid approach. We often start with a small pilot, collect data, then iterate on the model.

Deployment and ops matter as much as the model. Latency, reliability, and monitoring—especially in production environments like manufacturing or healthcare—can make or break an AI product. Plan for that from day one.

Ship, learn, iterate

Treat the first release as a learning release. Get it in front of users, measure the right things, and be ready to refine the model and the UX. The best AI-powered products get better over time because the team is set up to iterate.

If you're exploring how to build an AI-powered product and want a partner that's done it before, we'd love to talk.

Explore our Product Strategy, Custom Software, and AI Development services, or get in touch to discuss your project.