Embarking on a custom AI journey can be a significant investment. Yet, for many organizations, the rewards far outweigh the costs.
In industries where your operations are truly one-of-a-kind, or your data privacy is paramount, a custom AI solution can be the game-changer you’ve been seeking.
But let’s see first when do you not need custom solution?
- If an off-the-shelf product (e.g. a pre-trained ANN model) is available on the market, that solves our problem, it should be the preferred choice. It is sometimes even worth to consider whether you can adapt our problem to the available product by making minor compromises.
- You may find a free model that can work with some tweaking and fine-tuning. However, this can easily turn into a custom development, as you’d likely need to input your unique data into an existing framework.
- And, of course, if there exists a simple, non-AI solution to the problem. In such instances, that should generally be the chosen approach.
However, there are several situations where a custom AI development may be unavoidable:
- When your problem or requirements are highly unique, as your business activities are niche.
- If your priorities differ significantly from what existing AI model developers had in mind during the training process.
- When data security is paramount, and using an off-the-shelf or service-based solution means losing control over your proprietary data.
- The quality of currently available models does not meet your standards, and you believe you can create a superior solution
- Licensing terms of pre-built models are incompatible with your intended usage or business needs.
In these cases, investing in a tailored, custom AI development becomes necessary to address the nuances of your specific use case effectively while adhering to your priorities, security protocols, and quality benchmarks.
But why is it worth all the investment?
- Primarily, because it SOLVES our problem, which may not be solvable through other means.
- This AI-driven solution is often superior to traditional, non-AI approaches because it is specifically designed to meet our goals.
- If we’ve clearly defined our goals, the benefits will include significant cost savings and a competitive edge.
- A well-structured AI project usually includes a measurement methodology to evaluate the model’s effectiveness and the project’s success. While it’s possible to do this with traditional IT projects, it’s almost essential for AI projects.
While the journey may be more demanding, the destination is well worth the effort. By embracing custom AI development, you’re not just investing in a solution – you’re investing in the future of your organization.