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See Agentic Account Management in Action

A short walkthrough of how AI agents surface risk earlier, sharpen account judgment, and help teams act before “surprise” arrives.

No pitch deck. Bring one account you care about.

What this walkthrough shows

  • How signals become alerts before they become problems

  • How agents convert feedback into actions, not reports

  • How managers coach earlier with clearer decision options

Before...

  • Health shows up late, in averages

  • “Busy” sounds like fine

  • QBRs are backward-looking

  • Coaching happens after escalation

  • Playbooks are generic

After

  • Health is buyer-level and continuous

  • Silence and drift become signals

  • QBRs include forward risk and opportunity

  • Coaching happens before outcomes lock in

  • Actions are tailored to the account’s reality

Candy Cotton

A team of agents, each with a job

Humans stay accountable

  • Agents recommend and prepare,
    they do not own the relationship

  • Decisions are made with context and values, not scores alone

  • Autonomy is configurable...
    recommend, act within guardrails, escalate

Why teams trust this approach

Built for strategic accounts where buyer-level variation matters

Designed to drive action, not just measurement

Works alongside existing workflows, not outside them

Grounded in real client feedback and account operations

Choose your next step

We will map agents to your workflow, not demo screens.

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