Tag: Data & AI

Model Context Protocol (MCP) solves the real bottleneck in enterprise AI by standardizing how AI systems connect to tools, data and workflows. When combined with Progress Agentic RAG, it transforms retrieval into a reusable, governed capability, enabling AI agents to access trusted knowledge, compare sources and deliver grounded, traceable answers across multiple systems.

AI success in the enterprise is no longer about how powerful it looks in demos, but whether it can be trusted to operate reliably, transparently and at scale within real business workflows. Organizations that win will be those that prioritize governance, context and repeatability to turn AI from hype into dependable infrastructure that supports real decisions.

Progress MarkLogic FastTrack 2.0 empowers developers to build modern enterprise AI applications faster than ever to help organizations make actionable insight accessible to more people across the business.

Trust is now the differentiator: AI capability is rising fast, but enterprise adoption depends on governance, explainability and control. User-first beats tool-first: The winning model is bringing AI into the flow of work, not forcing people to learn complex tooling. Boring is what scales: Predictable, policy-aligned and auditable AI is what turns pilots into production outcomes.

AI fines are no longer theoretical; regulators are now enforcing control requirements as AI moves from pilots to production in financial services. The post explains why contracts alone won’t satisfy supervisors, what evidence regulators will expect to see in production and how organizations can operationalize governed, defensible AI with runtime guardrails, provenance, lineage and auditable controls—setting the agenda for the RegTech Conference in London on March 26.