Developing AI capabilities can transform your software... but may also blow your budget if the project isn’t properly managed.
The good news? There are strategies to harness AI value without breaking the bank.

1. Target high ROI use cases
Many companies fall into the trap of engaging in ‘AI for AI’s sake’.
The result: gimmicky features that are seldom used and expensive to maintain.
📌 Tip: Focus on 1 to 2 features that address a tangible problem for your users and deliver clear ROI.

2. Leverage existing tools
Building an AI model from scratch is costly in terms of data, infrastructure, and time.
An alternative: rely on existing AI APIs (LLMs, vision, speech-to-text...) and smartly integrate them into your software.
This saves on R&D while accelerating market entry.

3. Optimize infrastructure and usage
Hosting and inference costs can quickly escalate.
Use compressed models, batch processing, and select hosting that fits your volume of usage.

4. Test in real conditions before full deployment
A pilot on a small segment of users allows impact measurement before a full rollout.
This helps avoid large investments in poorly adopted features.

Conclusion & Rakam positioning
At Rakam, we assist software publishers in integrating AI in a targeted, measurable, and cost-effective way.
Our goal: maximize user value while controlling your costs and risks.