AI took center stage at Reltio DataDriven 2026, where global data and AI leaders aligned on one urgent priority: turning trusted, real-time, contextual data into scalable AI and measurable business impact. Reltio made a clear strategic bet: the next enterprise AI bottleneck isn’t model choice or orchestration but shared context – rebranding its platform around Context Intelligence and positioning Reltio as a System of Context that connects systems of record to agentic AI with governed, real-time intelligence.

CEO Manish Sood articulated a bold vision that moves Reltio beyond traditional “golden records” toward multi-hop reasoning across entities, relationships, interactions, and signals. The message was consistent across keynotes and breakouts: enterprises that fail to operationalize contextual intelligence will struggle to translate AI experimentation into sustained business impact.

That theme was reinforced in a fireside chat with Ansh Kanwar, Reltio’s Chief Product Officer, and Noel Yuhanna of Forrester Research, who emphasized the urgency of AI-ready data foundations, semantic layers, data fabric architectures, and real-time unification. Attendees left with a decisive message: AI success depends on unified, governed, real-time, contextual data, and the organizations that operationalize contextual intelligence today will lead tomorrow.

Key takeaways from the summit:

  • From MDM to AI-ready context intelligence. Reltio reframed from “MDM + 360 views” to a broader category claim: a Context Intelligence Platform that sits between systems of record and agentic AI. At its core, Intelligent Data Graph unifies entities, relationships, semantics, lineage, and consent. Customers should treat context as the foundation while rationalizing fragmented data, aligning semantics, and strengthening governance to scale AI.
  • Intelligent 360 strengthens the data foundation. Intelligent 360 delivers a graph-powered, unified view linking mastered entities with interactions and insights to drive analytics and AI outcomes. Advanced entity resolution through Flexible Entity Resolution Network (FERN) and Identity Builder increases precision, vector-based semantics, and transparency. This will be particularly helpful in unlocking high-impact use cases like segmentation, fraud detection, and churn mitigation.
  • AgentFlow is the inflection point. AgentFlow turns insight into execution with prebuilt and customizable AI agents. Included are an agent builder with governance/versioning/rollback, agent evaluation, BYO LLM, and MCP integrations. This shifts Reltio into the runtime conversation: not only serving context but orchestrating how agents use it with automated governance, data quality, and business workflows.
  • Real-time data is treated as non-negotiable infrastructure. Reltio emphasized that agentic AI cannot rely on batch updates or stale data. Its architecture prioritizes real-time unification, streaming integration, and dynamic entity resolution so both humans and AI operate on a continuously current view of the business. Customers must modernize legacy pipelines, eliminate latency, and embed governance directly into real-time flows for faster decisions, smarter automation, and measurable AI-driven outcomes.

Reltio’s narrative is compelling, but execution will determine whether System of Context becomes a durable enterprise control plane or simply an expanded MDM suite. The value hinges on customers’ ability to operationalize the full loop from contextualize → agentify → evaluate → improve, without rebuilding semantics and governance from scratch. Fragmented, poorly governed data is now a competitive liability. Enterprises that invest early in contextual intelligence will be best positioned to turn AI ambition into measurable business value.

Act now and build the trusted data foundation that enables AI to scale. We are here to help. Consider scheduling an inquiry/guidance session with us to further discuss this topic.