AI-driven communication intelligence, now available to the AI assistant you already use.
Every contact center leader knows the feeling. The question is simple — "How did Tier-2 support actually perform last quarter, and what changed?" — and the path to the answer is not.
You pull a queue report. Then an agent report. Then you export it, pivot it, cross-check it against sentiment scores, and try to remember whether the dip in week six was a staffing issue or a bad release. Two hours later you have a number. What you wanted was an explanation.
That gap between having data and understanding it is the problem Shadow Analytics has always worked on. Today we're closing it further.
What we built
Shadow Analytics MCP is a Model Context Protocol server for the Shadow Analytics platform. In plain terms: it lets an AI assistant talk directly to your communication intelligence — securely, in real time, using nothing but a question.
No dashboard hunting. No export-and-pivot. No BI ticket sitting in someone's backlog. You ask, and the analysis comes back written like an analyst wrote it.
What you can ask it
Point it at any slice of your ecosystem and it goes to work:
Any window of time. A single shift, a bad Tuesday, a quarter, a full year. Time is just part of the question.
Any part of the org. One team, one queue, one agent, or the whole ecosystem side by side.
Any single interaction. Right down to one call, followed end to end.
And what comes back isn't a table — it's intelligence:
- Call journey — one call, cradle to grave. Every hop, hold, transfer, and touchpoint across the ecosystem, assembled into a single continuous timeline instead of five disconnected reports you have to stitch together yourself.
- Pattern intelligence — the behaviors, cycles, and trends that don't announce themselves in a dashboard, because no one thought to build that view.
- Anomaly detection — what broke, when it broke, how far it deviates from normal, and whether it's still happening.
- Performance insight — agent, queue, and ecosystem health, measured against each other rather than in isolation.
- Customer experience — sentiment and CSAT read across real interactions, not just the surveys that happened to come back.
- Executive summary — the health of your communication ecosystem at a glance: where things stand, what moved, and what needs attention, written up so you could forward it to your leadership team without editing it first.
Why MCP matters here
Most analytics tools ask you to come to them. You log into their interface, learn their filters, and work within the questions someone else anticipated.
MCP inverts that. It's an open standard for connecting AI assistants to real systems and real data, which means Shadow Analytics stops being a destination and becomes a capability — available wherever your team already works and thinks. The tool comes to the question, instead of the question waiting for the tool.
Practically, that changes who gets to ask. A supervisor who would never open a BI platform will absolutely type "which of my agents is trending down on sentiment this month?" into a chat window. That's the unlock.
What this looks like in practice
You ask: "Compare Tier-1 and Tier-2 for Q2. Flag anything unusual and tell me what it cost us."
You get: A written analysis identifying a mid-quarter handle-time spike isolated to one queue, the sentiment decline that tracked alongside it, the agents most affected, the probable driver, and a short list of recommended actions — with the supporting numbers underneath.
Or go the other direction entirely — from the whole ecosystem down to a single call:
You ask: "Trace the call from the customer who escalated on Tuesday. Where did it go wrong?"
You get: The full journey, cradle to grave. Where it entered, how long it waited, who touched it, every transfer and hold, where sentiment turned, and the moment the experience broke.
That second question is the one that used to be nearly impossible. A call that crosses an IVR, two queues, three agents, and a transfer leaves its story scattered across systems that don't naturally talk to each other. Call Journey reassembles it into one timeline.
The difference isn't speed alone. It's that follow-up questions are now free. Why? Since when? Is it still happening? Show me the same thing for last year. Analysis stops being a report you commission and becomes a conversation you have.
Available now
Shadow Analytics MCP is built for the RingCentral ecosystem and available now.
If you're heading to the RingCentral Denver Tech Summit, August 17–19 at the Hyatt Regency DTC, come see it live — bring your hardest question about your own contact center and we'll point it at the data in front of you.
Better insights. Better decisions. Better outcomes.
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