Take AI from pilot to production, responsibly

VST’s AI Engineering practice is positioned around machine learning and generative AI embedded in enterprise workflows rather than isolated proofs of concept.

The scope includes predictive models, LLM applications and agents, enterprise search and knowledge assistants, copilots, intelligent automation and integration with CRM, ERP, service platforms and custom systems.

Model operations are part of the same proposition: evaluation suites, drift monitoring, cost and governance, alongside data readiness, guardrails, privacy and human oversight.

The intended outcomes are use cases that reach production, employees and customers served faster through copilots and automation, model quality, cost and risk made visible, and enterprise data made usable through search and assistants.

This line sits after application engineering in the lifecycle: intelligence is put inside systems that already have to ship, then evaluated with Quality Engineering for AI and GenAI rather than left as a demo.