AI Agents for GTM Operations

One set of numbers the whole team agrees on.

Sales says one number, customer success says another, and product has a third. These agents reconcile them, give every discrepancy an owner, and keep the definitions from drifting again.

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Every figure links back to the system and the record it came from.

The problem

Three tools, three answers, one meeting.

Someone asks how many accounts are actively using the product. Sales pulls one number from the CRM, customer success pulls another from the health dashboard, and product has a third from the analytics tool. All three are defended. All three are arguably correct, because nobody agreed what active means.

The meeting then spends forty minutes on whose number is right instead of on what to do. And it will happen again next month, because the definition was never written down anywhere that the tools can read.

You do not have a reporting problem. You have five definitions of the same word.

Agents

Three agents underneath the reporting

Foundation

Center of Excellence Agent

“Do the numbers agree, and is the program running?”

  • Reconciles the figure when two tools disagree, and says which one is right
  • Gives every finding an owner and a due date, then follows up
  • Sets the standards for tags, names, surveys and guides across teams
  • Lets anyone ask a plain question and get a chart back

The last point changes who can self-serve. Most reporting requests that reach an ops team are questions somebody could have answered directly if the data had been trustworthy.

Foundation

Pendo Audit Agent

“Can we trust the data underneath any of this?”

  • Tag coverage checked weekly, including releases that shipped untagged
  • Sub-accounts that never rolled up to a parent, and bad account metadata
  • Off-standard names, duplicate pages and duplicate events
  • Segments that are unverified, unused, or built on bad data

A baseline in days, then a standing check. This is the agent that finds out your Q3 numbers were wrong before someone presents them.

Inbound

Voice of Customer Agent

“Which accounts are asking, and what is it worth?”

  • Every request tied to the person, the account and the parent company
  • Demand sized by the revenue behind it rather than by mention count
  • Competitor mentions weighted by the spend of the account raising them
  • Themes across the whole book, not just the accounts that escalate

This turns the pipeline conversation from anecdote into something you can put a number against.

In the workflow

It shows up where the questions get asked

Slack or Teams

Ask a question in plain language, get a chart back, with the definition it used stated underneath.

Your dashboards

Reconciled figures, with each one linking back to the source system and record.

The review queue

Standards and definition changes go through your team. The agent proposes; you decide.

The point is not another dashboard. It is that the numbers on the dashboards you already have stop disagreeing with each other.

Baseline in days

not a quarter-long audit

Every figure

links to its source record

One definition

agreed and enforced

Guardrails

What it will not do

It will not change a definition on its own. It proposes, flags the disagreement, and waits for your team to decide.

It will not hand you a number you cannot trace. Every figure links to the source system and the record behind it.

It will not treat volume as importance. Ten complaints from one account count once.

It will not leave your environment. Your cloud, your data, and whichever model your security team has approved.

Other teams

The same agents, asked different questions

Product Operations

Tag coverage, naming, segments and access, checked on a schedule instead of before a board meeting.

Read more

Customer Success

Which accounts are getting value, which are stalling, and what the renewal conversation needs.

Read more

Product Marketing

Launch readiness backed by evidence, and positioning drawn from your customers’ own language.

Read more

Start with the number people argue about

Pick the metric your teams disagree on most. We will show you where the definitions diverge, which systems are feeding the gap, and what it takes to settle it.

Book a working session All Product Success Agents

FAQ

Common questions

Does this replace our BI tool?

No. It sits underneath it. The agents reconcile the inputs and the definitions so the reports you already run stop contradicting each other.

What happens when two teams genuinely disagree on a definition?

The agent surfaces the disagreement with both definitions and what each produces, then waits. Settling it is a decision your team makes, not one the agent makes for you.

Do we need Pendo for this?

The Pendo Audit and Center of Excellence agents do. The Voice of Customer Agent works with any call, ticket and survey data.

Who owns the findings?

Whoever you assign. The Center of Excellence Agent puts a name and a due date on every finding and follows up, which is the part that usually goes missing.

How long before this is useful?

A data baseline lands in days. Under two weeks from kickoff to a working agent on your own data.