We are selecting AI tools to build into our core operational workflows, but we are worried about getting locked into a proprietary platform that might go out of business or hike its prices next year. How do we build a tech-flexible AI stack?

Question

Tyler Smith · Accepted Answer

To build a tech-flexible operations stack, you must separate your workflows from the specific AI models that power them. Relying too heavily on a single, highly customized niche AI software platform leaves your business vulnerable to price increases, poor service, or sudden vendor insolvency.

The solution is to design your automated workflows using standard middleware platforms that can easily swap out underlying AI models. Use integration platforms to connect your existing core business software to major, secure AI APIs.

By using middleware, you retain ownership of the workflow logic. If the AI model you are currently using becomes obsolete or too expensive, you can simply change the API connection to a different provider without having to rebuild your entire operational system from scratch.

Additionally, focus heavily on documenting your processes in your company playbook. Your intellectual property is not the specific AI tool you use, but the operational logic, the custom instructions, and the clean data inputs that you have created. Keep a secure repository of all your custom prompts, workflow diagrams, and data schemas.

When you own the process logic and the data, the AI model itself becomes a utility. You can easily plug in the best and most cost-effective technology as it evolves, ensuring your business stays agile and protected from vendor lock-in.