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How do we connect our companies AI infrastructure to Infinity?

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How do we connect our companies AI infrastructure to Infinity? I'd like to utilize its knowledge sources, prebuilt prompts, and custom agents. Is there an API or MCP server I can connect to as a member? What's the price?

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Luis Branco CEO| Business Insight, Consultores de Gestão, Ldª Carcavelos, Lisboa, Portugal
This is a very relevant question, especially as more organizations move from experimenting with AI tools to designing structured AI architectures.

From what is publicly visible, PMI Infinity currently appears to function as a member-facing assistant rather than as an enterprise integration platform.
I have not seen publicly documented APIs, MCP endpoints, or formal enterprise connectors that would allow direct infrastructure-level integration.

That said, your question highlights a broader architectural issue.

There is a material difference between:

• Using an AI assistant through an interface
• Embedding AI capabilities into a governed organizational ecosystem

For enterprise-grade integration, organizations typically require:

• Secure API access
• Clear authentication and authorization layers
• Data boundary definition and IP governance
• Auditability and traceability
• Pricing models aligned with organizational deployment

Without those elements, integration into corporate AI infrastructure becomes structurally complex.

It would be helpful if PMI clarified publicly:

  1. Whether enterprise API access is planned
  2. Whether integration standards such as MCP are being considered
  3. What the commercial model would look like for organizational use
The demand is understandable.
The key issue is not only access, but governance, architecture, and accountability at scale.

That distinction is strategic.
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1 reply by Joshua Raveling
Feb 18, 2026 11:03 AM
Joshua Raveling
...
My company has a very mature AI infrastructure, I would say bleeding edge from a lot of the talk. So I’d be very interested in talking with you directly about this.
avatar
Shirendev Enkhtsetseg Velky Beranov, Czechia
Interesting question. Before connecting AI infrastructure, it helps to clarify data sources, security requirements, and integration method (API, middleware, or cloud). Most enterprise AI platforms provide API documentation, authentication, and pricing based on usage. A pilot integration first is usually the best approach before scaling. Hope this helps.
avatar
Kerry Brooks
PMI Team Member
AI Product Manager (B2B) for PMI| Project Management Institute (PMI) Middletown, DE, United States
Hi! I'm the B2B product manager on the PMI Infinity Team. Connecting your organization's AI infrastructure to Infinity — including access to knowledge sources, prebuilt prompts, and custom agents — is something we're actively exploring. We currently have a version of Infinity in pilot with select organizations, and a big part of that program is learning about organizational needs: the integrations that matter most, the workflows you're trying to support, and the platforms (like API or MCP connectivity) that would make Infinity truly useful at scale.

To be transparent: these capabilities, including any API or MCP integration options, are not yet developed or commercially available, but experimentation is in progress. We want to get this right before we bring it to market, and feedback from practitioners like you is shaping exactly what we build.

Stay tuned for more updates as we move through 2026!
Feb 18, 2026 4:57 AM
Replying to Luis Branco
...
This is a very relevant question, especially as more organizations move from experimenting with AI tools to designing structured AI architectures.

From what is publicly visible, PMI Infinity currently appears to function as a member-facing assistant rather than as an enterprise integration platform.
I have not seen publicly documented APIs, MCP endpoints, or formal enterprise connectors that would allow direct infrastructure-level integration.

That said, your question highlights a broader architectural issue.

There is a material difference between:

• Using an AI assistant through an interface
• Embedding AI capabilities into a governed organizational ecosystem

For enterprise-grade integration, organizations typically require:

• Secure API access
• Clear authentication and authorization layers
• Data boundary definition and IP governance
• Auditability and traceability
• Pricing models aligned with organizational deployment

Without those elements, integration into corporate AI infrastructure becomes structurally complex.

It would be helpful if PMI clarified publicly:

  1. Whether enterprise API access is planned
  2. Whether integration standards such as MCP are being considered
  3. What the commercial model would look like for organizational use
The demand is understandable.
The key issue is not only access, but governance, architecture, and accountability at scale.

That distinction is strategic.
My company has a very mature AI infrastructure, I would say bleeding edge from a lot of the talk. So I’d be very interested in talking with you directly about this.
avatar
Lissette Indhira Pimentel Sosa
Community Champion
Program Manager| HARPER SRL Santo Domingo / Distrito Nacional, Dominican Republic
Joshua, if your AI infrastructure is already mature, engaging with the Infinity pilot team could be a strong strategic move.
Early collaboration often shapes integration models and enterprise capabilities. It may be worth connecting directly to explore alignment and next steps.

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