By 2025, integrating AI into software won't just be a marketing 'plus'; it’s a strategic decision that can either strengthen or weaken your product.

Yet, too many teams add AI features because 'everyone else is doing it'... and end up with high costs, extended timelines, and little return on investment.

At Rakam, we see 3 straightforward steps to discover AI features that truly matter.

1. Start with your users' real needs

Don’t start with “What AI can we add?” but rather “What costly or recurring problems do my clients face?”

• Analyse your support tickets.

• Listen to your sales team.

• Observe your clients in real-life situations.

This is where AI can have the greatest impact.

2. Prioritise business impact over technical complexity

A good AI feature is measured by:

• Time savings for the user.

• Error reduction or unnecessary steps cut.

• Additional revenue generation (upsell, new clients).

The most sophisticated algorithms are useless if usage remains marginal.

3. Test quickly before making heavy investments

Build a targeted prototype that:

• Connects to your existing data.

• Shows value in days, not months.

• Lets you decide if full-scale development is worth the investment.

💡 Rakam Example:
For a logistics client, we identified that 80% of support calls were about parcel tracking.
A simple AI automated response feature reduced calls by 60%—even before a full predictive engine was developed.

Conclusion

Discovering a good AI feature isn't about following a trend, it’s about solving a client problem in a measurable way.

Rakam assists SaaS providers in:

• Analysing their usage data.

• Identifying high-value AI use cases.

• Rapid prototyping that complies with European legal frameworks.

Want to know which AI features could truly boost your SaaS?
Schedule a diagnostic with our team.