AI Solutions: Agents, MCP, and Operational AI
AI agents, small language models, and EU AI Act compliance shaped enterprise AI delivery in 2025.
In 2025, enterprise AI moved from experimentation to operational deployment. Teams combined AI agents with small language models (SLMs) for cost-effective, domain-specific tasks — document triage, workflow assistance, and internal knowledge retrieval — embedded inside existing applications rather than standalone chat windows.
Agents and MCP
Agentic workflows orchestrated multi-step tasks: gather context, propose actions, execute through approved tools, and log outcomes. The Model Context Protocol (MCP) standardised how agents connected to CRMs, ticketing systems, and custom APIs without ad-hoc integrations. Human approval remained mandatory for high-risk decisions in regulated sectors.
Edge AI and MLOps
Edge AI ran inference on devices or regional nodes where latency, privacy, or connectivity constraints mattered — factory floors, mobile field apps, and on-prem document processing. MLOps practices — versioned datasets, reproducible pipelines, drift monitoring, and rollback paths — separated pilots from production. Azure ML, AWS SageMaker, and open-source stacks supported end-to-end lifecycles.
EU AI Act compliance
With the EU AI Act entering operational enforcement, organisations documented risk classifications, training data provenance, and oversight procedures. Explainability and audit trails mattered in finance, healthcare, and public sector programmes.
PrequaliQ focuses on AI that attaches to real business processes — with clear metrics, maintainable pipelines, and governance appropriate to your industry.