Every release, I ask the team the same question: Does this move the line? 

With 2026 R2, the answer is yes, and I think it moves it in a direction that changes the conversation about what MDM implementation actually looks like. 

The Big Shift: Aisey as the Orchestration Layer 

The architectural story in R2 is Aisey’s agentic framework. 

Aisey has always been designed as an orchestrator. In R2, that design becomes fully realized. Aisey is built on the Microsoft Agent Framework, with a growing fleet of specialized agents that have access to Profisee documentation and best practices. Taken together, Aisey is knowledgeable in the platform the way a trained expert would.  

Here’s what that looks like in practice. An admin uploads a Word document describing their data requirements. Aisey reads it, orchestrates Profisee specialist agents covering data modeling, integration, matching, data quality and stewardship, and delivers a fully configured MDM environment. The whole thing takes about 10 minutes. 

I want to be precise about what “autonomous” means here. Aisey handles approximately 90% of the configuration work without manual input. There is intentional human involvement along the way where we believe human judgment belongs, and everything she does can easily be reviewed and tweaked. But the expert-led, time-intensive work of standing up an MDM environment? That’s now Aisey’s job. 

R2 also grows Aisey skills and capabilities. Admins configure through natural language conversation. Stewards get answers in the platform, in the moment. Describe what you need, and Aisey builds it. 

This is the release where Aisey becomes the primary way the platform gets configured.  

MCP: Making Governed Data Available Everywhere 

MCP (Model Context Protocol) is how Profisee exposes mastered data to the broader AI ecosystem. In R2, the Profisee MCP server expands significantly so that both users and unattended agents can natively interact with master data from Profisee as part of their AI task flow. 

Matching Lookups and Strategies, Connect Service Providers, FastApps, Forms, and Presentation Views all now surface through MCP. Every modern AI platform, Microsoft Copilot, Claude, ChatGPT, custom agents, enterprise AI frameworks, etc., can access current, governed master data through a single secure interface. Governance, authentication and audit are built into every interaction. 

As organizations build out agentic AI workflows, the question they keep hitting is whether the data feeding those agents can be relied on. Profisee MCP is the answer to that question, delivering governed, trusted data to AI workflows.  

Integration: Any System, Configured in Conversation 

Connect continues to evolve in R2, and two things in particular stand out. 

On-demand connector generation is now available. Describe the target system to Aisey and Aisey generates the provider.  You can build connectors tailored to your actual data model through natural language with no code required. 

R2 brings deeper operational control and greater flexibility to Connect. Your team can manage integrations more precisely, respond faster when something needs attention, and trigger Connect directly from stewardship workflows. 

The result is an integration engine that lets you connect, configure, and control any integration strategy across any source. 

Governance: Native, Continuous, Enterprise-Ready

We invest in governance to keep pace with the regulatory and operational demands of your organization. R2 reflects that. 

Data quality gets more powerful and more precise. Stewards have greater control over how validation rules behave as data requirements evolve. Compliance capabilities deepen with a full transaction audit trail accessible in the web and via API, and security improvements help meet the requirements of the modern enterprise.  

Matching: Scale and Visibility, Together 

At enterprise scale, matching has to work. We now regularly benchmark Profisee on hundreds of millions of records to ensure your most complex, high-volume data environments are covered. 

But scale without visibility is incomplete. R2 adds real-time Match Monitoring to deliver a live view of strategy execution, resolution rates, and failure states. Matching Strategy Status is accessible via API. Operations teams can see what’s happening as it happens, and act before downstream systems are affected. 

This combination of proven scale and operational transparency ensures your matching performs when and where it matters most. 

What’s Next 

Our 26R3 release is next, as we continue to release quarterly. 

Aisey skills extend platform-wide. Every administrative area — Hierarchies, Accounts and Teams, Modeling, Relationships — becomes conversational. If you can configure it today, you’ll be able to configure it through Aisey just a few months. 

AI Agents take autonomous action. Proposed Match Review, Survivorship, and DQ Stewardship Filtering will have autonomous agents. The goal is to shift your team’s attention toward decisions that genuinely require human judgment and let the agents handle the rest. 

Available Now 

Profisee 2026 R2 is generally available July 7, 2026.