Built for How Executives Actually Operate

We kept noticing the same moment in key revenue conversations.

A strategic deal that was expected to close this quarter suddenly went quiet. A commit number that felt solid a week ago no longer did. A key opportunity slipped, and now the conversation shifted from forecast to recovery.

That’s when the questions surfaced.

When did this start to turn? Did stakeholder engagement drop earlier than we realized? Were we expanding the buying group, or narrowing it? What does the team need to do right now to recover this deal?

The questions were clear. The answers were not.

What Gets in the Way

When a deal pushes to next quarter, a competitor enters a late-stage deal, or a legal review goes quiet, the answers surface through conversations and recaps, not in any single place.

Inputs are useful, but they are summaries. Important signals live in the underlying activity like meeting frequency declining over several weeks, response times stretching, a senior stakeholder attending fewer calls, a shift in tone in email threads.

Those inputs don't become answers on their own - someone still has to assemble them, interpret them, and chase down what's missing. When clarity arrives late, you make reactive decisions. When clarity arrives early, you can steer.

That difference changes outcomes.

What We Realized

The answer was not another place to go or person to ping. You already have places where you think through decisions. What was missing was direct access to the complete activity record behind the number, without reconstructing it through live conversations every time something feels off.

That’s where MCP comes in.

What Changes with MCP

Model Context Protocol (MCP) is an open standard that allows AI agents to securely access external data sources. People.ai's MCP Server connects to the complete activity record captured automatically across your revenue organization.

When you ask your AI Agent of choice about a deal, the response is grounded in the full history of emails, meetings, conversations, and engagement patterns, not just CRM fields or secondhand summaries. The AI reasons over what actually happened across the revenue process.

This changes how you use AI. It becomes a direct view into the activity behind your forecast.

The result is confidence that your decisions reflect the full record.

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Where This Shows Up Day to Day

When a large opportunity shifts, you can see whether engagement declined gradually over several weeks or dropped abruptly after a pricing conversation. When your forecast changes, you can understand which deals lost momentum and whether coverage behind the commit is expanding or contracting. When preparing for the board, you can speak to the health of pipeline based on documented activity, not recollection.

As Andrew Brown, CRO at Red Hat, shared:

“People.ai's open architecture using MCP fits perfectly with our vision to become an AI-enabled enterprise. Our sales team now has the intelligence they need to make informed decisions, resulting in win rates that improved by over 50 percent.”

Why This Matters Now

As AI becomes part of how executives operate, speed alone is not an advantage. The quality and completeness of the underlying activity determine whether AI becomes a source of clarity or noise.

MCP is our way of closing that gap by connecting the tools you already use to the activity record behind their business.

We built it because this is how teams already work. The technology needed to catch up.