AI Solutions: From ChatGPT Buzz to Production Guardrails
GPT-4, Azure OpenAI, early RAG adoption, and EU AI Act discussions shaped how enterprises moved generative AI from pilots to governed workflows.
2023 was the year enterprise AI conversations shifted decisively toward large language models. ChatGPT and GPT-4 made generative AI tangible for every boardroom — but production success still depended on narrow use cases, solid data boundaries, and human oversight.
Practical deployment patterns
Teams paired Azure OpenAI or private endpoints with retrieval-augmented generation (RAG) so answers cited internal documents instead of hallucinating policy. Copilots appeared in support, HR, and engineering workflows — always with logging, access control, and escalation paths.
MLOps meets LLMOps
Versioned prompts, evaluation sets, and monitoring for drift extended familiar MLOps discipline. Pilots that lacked rollback plans rarely survived first contact with real users.
Regulation and trust
EU AI Act discussions pushed organisations to classify risk, document training data sources, and define human review for high-impact decisions — especially in finance and public sector contexts.
PrequaliQ focuses on AI that attaches to real business processes — with clear metrics, maintainable pipelines, and governance appropriate to your industry.