Nexa runs two client practices. AI Consulting determines where AI produces return and what it costs. AI Engineering builds the system and deploys it into the client's environment.
An engagement can start with either practice. The assessment specification becomes the brief for the first build.
A fixed-scope assessment of data, workflows, and systems that returns a ranked, costed, and sequenced roadmap the client owns, with governance and model selection where the roadmap requires them.
View AI ConsultingCustomer-facing AI products and internal AI systems built to a written specification by ML engineers, software engineers, product managers, and designers, then deployed in the client's environment.
View AI EngineeringFour terms apply to every consulting and engineering engagement.
A 30-minute call establishes the problem, the users, and the systems the work must integrate with.
Deliverables, timeline, and acceptance criteria are fixed in writing before engineering starts.
ML engineers, software engineers, product managers, and designers work alongside the client's team for the length of the engagement.
Code, configuration, documentation, and roadmaps produced in the engagement belong to the client.
Send a short description of the operation and the problem. A 30-minute scoping call follows.