Technical, commercial, and operational FAQ.
Clear answers to the essential questions engineering and executive leaders ask when evaluating an AI systems partner.
Architecture & Implementation
How do you price an AI implementation project?
The commercial model is agreed per project, before work starts. Time and materials is one option. The shape depends on the system, the integrations, and how long you want us involved after launch.
What is the typical timeline for an AI Lab implementation?
It depends on the system. A first working version is often a few weeks. Connecting it to your existing tools takes longer. We give a timeline after we understand the job.
Who owns the code and intellectual property?
You do. All source code, orchestration logic, evaluation datasets, infrastructure scripts, and documentation developed during the engagement are fully assigned to your organization upon payment.
Do you host the AI systems, or do they deploy into our cloud?
We deploy systems directly into your cloud infrastructure (AWS, GCP, Azure, or private data centers). We configure infrastructure-as-code (Terraform, Docker, Kubernetes) so that your team maintains total control over networking, security groups, and data storage.
How do you guarantee that our confidential company data remains secure?
We adhere to strict data isolation protocols. We utilize enterprise API tiers with guaranteed zero data retention (ZDR), or deploy self-hosted open-source models inside your private VPC. Your proprietary data is never used to train or fine-tune public foundation models.
What happens after the system goes live in production?
We hand over the code, the documentation, and the tests so your team can run it. If you want us to stay, that is part of the agreement and can continue as time and materials.
Can AI Lab integrate with our existing engineering and DevOps workflows?
Yes. We build directly within your existing repositories, adhere to your CI/CD delivery pipelines, and comply with your internal architecture, security, and coding standards. Our systems engineers conduct joint sprint reviews with your technical leads to ensure a frictionless production deployment.
Ready to discuss your AI architecture?