An AI system is not a one-time purchase you make and forget. You build a relationship with the vendor: for maintenance, updates, support and the ongoing development of the system. That relationship lasts years. A vendor that performs well in the sales phase but disappoints in the collaboration costs you far more than just the money from the initial investment.

Moreover, AI systems depend on the stability and reliability of the vendor. If a vendor changes its model, shuts down or is acquired, that has direct consequences for your system.

The first question is whether the vendor's technology is genuinely suited to your specific use case. Ask for a proof of concept on your data, not on their example data. Assess the output for accuracy, consistency and usability in your context.

Watch for hidden limitations. How much data can the system process? How does it perform in languages other than English? What are the latency figures under higher load? Technical due diligence is not a side matter.

Any AI vendor that processes your personal data or that of your customers must comply with GDPR. Ask about the processing location of your data: is it stored within the EU or outside? Which sub-processors are involved? Is a data processing agreement available?

Also ask about security measures: encryption at rest and in transit, access control, incident response procedures. Certifications such as ISO 27001 or SOC 2 indicate security maturity but are not a guarantee.

Can you understand what the AI system does and why it produces certain outcomes? For some applications, explainability is a legal requirement (GDPR Article 22). But even when it is not legally required, you as a customer want to be able to understand when the system is functioning well and when it is not.

Ask how the vendor handles model updates. Are you informed when the model changes? Can you decline an update? Changes to the model can have unexpected consequences for your application.

Read the contract carefully, including the fine print. Pay attention to: who owns the data you bring in? May the vendor use your data to train its model? What are the notice periods? Is there an exit clause enabling you to export your data when you end the collaboration?

Also ensure clear agreements on SLAs: availability, response times for incidents and maximum downtime. Vague promises in sales conversations must be converted into contractual obligations.

AI startups come and go. A vendor that exists today may not be around in two years. Ask about the company's funding, how long they have been operating and whether they are profitable or dependent on external financing.

This is not a reason to choose only large, established parties. But it is a factor to weigh, especially when building a multi-year dependency.

The best technology from the wrong partner is a poor choice. How responsive is the vendor during the sales process? How do they handle critical questions? Are they willing to facilitate a reference check with existing customers?

A sales conversation is a preview of the relationship. If communication is already slow or questions are being deflected, that rarely improves after the contract is signed.

Mach8 does not operate as a vendor selling a standard solution. We work as a partner that understands the specific situation of your organisation and based on that chooses the most suitable approach. Sometimes that means using existing platforms, sometimes it means custom development.

Evaluating AI vendors requires more than comparing features and prices. Technical suitability, privacy, contractual certainty, financial stability and the quality of the relationship are all relevant. Take the time for a thorough selection process.

Want to know how Mach8 supports you with vendor selection or with implementation? Get in touch or view our AI agents service.