AI Agents for Customer Success

Know which accounts are stalling before the renewal call.

Six agents across the account lifecycle — health monitoring, renewal prep, QBR generation, leadership visibility, CSM coaching and product signal. Running on your data, with the CSM deciding what happens next.

Every score shows its work. No black-box health number.

The problem

The health score nobody believes.

Most health scores are built from logins and ticket counts because those were the fields available, not because they predict anything. Everyone on the team knows which accounts are actually at risk, and they know it from a call they half remember rather than from the dashboard.

Meanwhile the evidence is sitting there. The renewal conversation that went quiet, the admin who left, the three tickets about the same workflow, the feature a customer asked for eight months ago that shipped last week and nobody told them. It is all recorded. None of it reaches the CSM in time to matter.

A risk score you cannot explain is a rumor with a number attached.

Agents

Six agents across the customer lifecycle

Each one does reading and assembly that a CSM or manager would otherwise do by hand, in the half hour before it is needed.

Risk & visibility

Customer Health Monitoring Agent

“Which accounts are drifting, and which are ready for more?”

  • Reads CRM data, support activity, product usage and interaction history
  • Surfaces churn risk before a human review cycle would catch it
  • Flags expansion opportunity off the same signals
  • Shows the behaviour behind every score, not just the number

Earlier is the whole point. A risk found at the quarterly review is a risk found late.

Renewal intelligence

Renewal Prep Agent

“What does the CSM need to know before this renewal call?”

  • Health history, and how it moved across the term
  • Open tickets, and what is still unresolved
  • Usage trends against what the account bought
  • The context from prior conversations, carried forward

The brief is ready before the call rather than assembled in the thirty minutes in front of it, out of five systems.

QBR automation

QBR / EBR Generation Agent

“Can the account review write itself from live data?”

  • Usage signals and support trends, pulled as the review is written
  • Prior conversations, and the initiatives still open
  • A draft your team edits rather than builds from a blank page

The time goes into the conversation with the customer instead of the deck in front of it.

Management visibility

CS Leadership Command Center

“What across the book needs intervention this week?”

  • Renewals inside ninety days
  • Low-engagement accounts, and support burden that is climbing
  • Implementations that have stalled
  • The conditions that need a manager, surfaced without digging

One operating view across the book, so intervention is a decision rather than a discovery.

Team development

CS Coaching Agent

“How does a manager coach the whole team, not just their own accounts?”

  • Reads the call transcripts you already record
  • Drafts coaching notes, scored against your playbook
  • Finds the patterns that repeat across the team

A manager can coach consistently at scale instead of only on the calls they personally sat in on.

Product signal

Workaround & Product Intelligence Agent

“What are customers working around, and what is it costing?”

  • Captures the asks that keep coming back
  • Categorizes the workarounds teams have built to cope
  • Sizes the impact of each one

Then leadership decides what to document, standardize, escalate, or take to product as a real conversation.

In the workflow

It shows up where the CSM already works

Your CRM

Health signals and renewal briefs land on the account record, with the evidence behind each one attached.

Slack or Teams

A renewal moved inside ninety days. Support burden is climbing on an account. An implementation stalled.

The review queue

One screen to confirm, edit or reject a brief, a QBR or an outreach draft before it goes anywhere.

The agent never speaks to your customer. It gets the CSM into the conversation prepared, with the evidence already assembled.

Under 2 weeks

kickoff to a working agent

Every QBR

built from live data, not slide work

Every score

shows the behavior behind it

Guardrails

What it will not do

It will not email your customer. Every outreach, brief and review is a draft until the CSM approves it.

It will not hand you a risk score you cannot explain. Each one shows the behavior, the account and the evidence underneath.

It will not grade your CSMs behind their backs. Coaching notes go to the manager and the rep, scored against your playbook rather than a generic rubric.

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

Run it against your own book

Bring a segment of your accounts with their calls, tickets and usage. We will show you which ones the agents flag, what moved each score, and what the renewal brief would have said.

FAQ

Common questions

Does this replace our health score?

Usually it replaces what the health score was trying to do. Most scores run on logins and ticket counts because those fields were available. The Customer Health Monitoring Agent scores on behavior that ties to retention, and shows the evidence for each one.

Where does the QBR content come from?

Live data — usage signals, support trends, prior conversations and open initiatives. The agent assembles the draft. Your team edits it and decides what the story is.

Will it contact customers on its own?

No. Every note, brief, review and outreach is a draft until a named person approves it.

How does the coaching agent handle call recordings?

It reads transcripts you already record and scores against your playbook, not a generic rubric. Notes go to the manager and the rep. It is built to let a manager coach across the whole team rather than only the accounts they sit in on.

Do we need Pendo for this?

The agents that read product usage — health monitoring, renewal prep and QBR generation — need usage data, and Pendo is the most common source. The coaching and product intelligence agents work from calls, tickets and transcripts.

How long before a CS team is using this?

Under two weeks from kickoff to a working agent on your own data. A pod stays with your team until it is in weekly use.