Frequently asked questions about choosing an AI vendor
20 questions
How do you choose an AI development company?
It’s worth assessing real experience, integration capability, security, architecture, evaluation, maintenance and understanding of the process.
What should I ask an AI vendor before hiring?
A clear explanation of the problem, the proposed architecture, the data needed, risks, integrations, success criteria and maintenance.
Is a standard platform or custom development better?
It depends on the process. If a platform covers the need well, it’s usually more efficient. Custom development makes sense when there are specific requirements.
What questions should I ask before implementing AI?
What problem it solves, what data it uses, what mistakes it can make, which systems it touches, who supervises it and how the result is measured.
Does it matter that the vendor understands business processes?
Yes. The quality of a solution depends as much on understanding the process as on choosing the technology.
Should a company start with a small project?
It can be a good idea when there’s uncertainty and you want to prove value before scaling up.
What signs show a project is badly scoped?
Starting from a technology without a defined problem, not measuring results, ignoring exceptions or not defining permissions and limits.
What does taking AI to production mean?
It means building it into a real process, with users, data, controls, monitoring and maintenance.
What’s the difference between a demo and a system in production?
A demo tests an idea. A system in production has to handle errors, exceptions, permissions, security, costs and real use.
What should happen after launch?
Monitor behavior, fix errors, review costs, analyze new needs and improve the system with real data.
What experience should an AI vendor be able to show?
Experience with real systems, integrations, error handling, security, evaluation and maintenance.
Is knowing how to write prompts enough?
No. A business system requires architecture, software, integrations, permissions, data and monitoring.
What’s the difference between an automation agency and an AI development company?
What sets a vendor apart isn’t what it calls itself. Ask whether it measures quality before every change, whether the code is owned by your company and whether it keeps monitoring the system after delivery.
What should a technical proposal include?
Goal, scope, integrations, architecture, risks, success criteria, maintenance and costs.
Does it matter to name an internal project owner?
Yes. Having one person in charge makes decisions, data access and adoption easier.
What signs show a vendor is selling hype?
Promises of total automation, no metrics, little attention to exceptions or no clarity on limits and security.
Should a good vendor advise against using AI in some cases?
Yes. Choosing conventional software when it’s enough usually signals better technical judgment.
How can I tell if a vendor understands the business?
It should be able to explain the process, its exceptions and the success criteria before talking only about technology.
What happens if a project changes scope?
The technical impact, budget, timelines and integrations must be reviewed before expanding it.
Is it a good idea to document the architecture?
Yes. It makes maintenance, auditing, evolution and knowledge transfer easier.
Tell us about the process you want to improve.
You do not need to know which model to use, which architecture you need or whether the problem calls for an AI agent. Tell us how the process works today, who is involved and which tools you use.
We’ll reply within one business day with a first read of your case.