At Datakami, we view our relationships with clients as partnerships. Projects are active and open collaborations.
We're here to offer you solid expertise and the best advice for your specific product and situation. Expect a pragmatic approach and actionable advice that you can put to use right away. And if we notice new developments in applied AI that might be relevant to you, we'll let you know.
During projects, we give regular updates about our progress. We favor asynchronous communication to keep the communication overhead to a minimum. After a project, we give you everything you need - data, code, and infrastructure - all in plain English, so you can take the work forward without needing us to hold your hand.
Datakami is bootstrapped and completely independent from any vendor. If we think you should take a particular approach or there's a better tool for the job, we'll tell you. We'll also help you reduce your reliance on third parties where possible, so you can keep control over your product. We favor open-source software, transparent models and open data.
We understand that it is scary for businesses to show their intellectual property to contractors. That makes sense. However, as your ML engineers, we need to understand your product, down to the finest technical details. We keep anything you share with us, such as data or code, strictly confidential.
We make sure that working with us does not take up much of your time. Sometimes, we'll need things like data or code from you. Quickly replying to our requests makes sure we can keep the project moving.
You know your business better than anyone. Show us the nuts and bolts of your product, so we can really understand the problem. Don't be afraid to discuss the things you've tried in the past that didn't work. Share your thoughts.
Generative AI is a young field, and models and tools are changing on a daily basis. The outcome of a project is often uncertain, especially when we develop a new AI product or work with brand-new models. Not everything we will try will work. To deal with this, we work in an iterative way. Sometimes we need to adjust our project goals based on progressive insight of what works and what won't. If you are aware of the unpredictability of innovation, we can work together more smoothly.