---
title: "How to Choose an AI Development Partner | Azendo"
description: "Seven questions worth asking any AI development partner before you sign, from evaluation sets to what happens when your model provider deprecates."
url: "https://azendo.co/blog/ai-engineering/how-to-choose-an-ai-development-partner/"
---

[Newsroom](https://azendo.co/newsroom/) [AI engineering](https://azendo.co/blog/ai-engineering/) 

# Seven questions to ask any AI development partner.

Choosing an AI development partner is harder than choosing a software vendor, because the failure modes are less visible. A badly built web application is obvious in a week. A badly built retrieval system looks fine in the demo and degrades quietly for a year. These are the questions that separate them.

By Mikkel Schmidt  18 September 2026 

A partner who has run AI in production answers with a story about something that broke.

## What to ask before signing

**How will we know if quality drops?**If the answer does not involve an evaluation set, there is no answer. Ask to see one from a previous engagement.

**What happens when the model provider deprecates?**It will happen inside your engagement. Ask how they have handled a migration before.

**Who owns the prompts, the evaluation data and the code?**It should be you, all of it. Some arrangements quietly keep the evaluation set with the vendor, which makes leaving expensive.

**How is token spend monitored?**Costs move in the wrong direction quietly. Ask who watches it and what triggers an alert.

**What happens after launch?**Most AI engagements are priced to deliver a feature. Ask explicitly what the arrangement looks like in month twelve.

**Can this run inside our infrastructure?**If your data cannot leave, ask about open-weight models early rather than after scoping.

**Who is actually doing the work?**Ask whether the people in the pitch are the people assigned, and whether they stay assigned.

The ongoing work after launch — evaluation, monitoring, retraining — is covered under [managed AI services](https://azendo.co/services/ai-engineering/).

## Reading the answers

The pattern to listen for is specificity. A partner who has run AI in production will answer with a story about something that broke. A partner who has not will answer with capability language.

What Azendo delivers under this model is set out under AI engineering services.

Two of the seven questions are really about the data rather than the model, and a partner who cannot answer them usually needs [managed data services](https://azendo.co/services/data-engineering/) more than another AI engineer. The commercial shape of the engagement matters as much as the technical answers, and [staff augmentation vs managed services](https://azendo.co/blog/engagement-models/staff-augmentation-vs-managed-services/) sets out which of the two you are actually being sold.

## Questions people ask.

What is the difference between an AI development partner and an AI consultancy? 

Roughly, whether they stay. Consultancies advise and hand over. A partner is assigned to the product and remains accountable for how it behaves after launch.

How much should AI engineering cost? 

It varies too much by scope to quote usefully. What is worth comparing is whether the price includes the post-launch work, because that is where most of the real cost sits.

## Tell us what the roadmap needs and we will tell you what it takes.

A service delivery manager replies with the disciplines we would assign, the monthly capacity and what the first month looks like.

[Get in touch](https://azendo.co/get-in-touch/) [How it works](https://azendo.co/how-it-works/) 

## Tell us what your AI roadmap needs.