12 Account Growth AI Agents, Live in Production.
12 live agents automate account growth within sales. 1 runs on a schedule, 9 run on demand and 2 run when a message arrives. Each one publishes the inputs it needs, the steps it works through and what it hands back.
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Churn Signal Detection
Upload account health data and get the accounts showing churn signals, what each signal actually is, and which ones are an expansion opening in disguise.
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Customer Segmentation
Upload your customer base and get it divided into segments that emerge from the data, each with what defines it, what it is worth, and the one motion that fits it.
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Inquiry Triage
Answer the routine questions that reach a sales inbox from your own approved material, and route everything else to a person rather than guessing.
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Missing Data Collection
Work out which missing customer fields are actually worth chasing, who would know each one, and draft the request — instead of sending a blanket form.
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Objection Early Warning
Read a customer message for the objection underneath it — what is actually being raised, how serious it is, and the response your own material supports.
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Offer Personalization
Describe the customer and get two or three bundles built for them specifically, each with what is in it, what it costs, and who inside the account it is aimed at.
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Post-Proposal Engagement Read
Upload what happened after the proposal went out and get an honest read on intent — which signals mean something, which mean nothing, and what the silence actually tells you.
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Product Fit Signals
Read what a customer's behaviour says they need next, and separate a real signal from a coincidence before anyone acts on it.
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Profile Completeness Monitor
Score how trustworthy each customer profile is — not just whether fields are filled, but whether what is in them is recent enough to act on.
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Upsell Interaction Audit
Check that every upsell conversation left a record — what was offered, what was agreed, and who approved it — so nothing sold sits outside the audit trail.
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Upsell Prioritization
Upload a customer usage export and get accounts ranked by expansion potential, the segments behind them, and a playbook for the top opportunities.
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Upsell Proposal Routing
Route an upsell proposal to the right approver with the account's risk in view — so nobody approves an expansion into an account that is quietly in trouble.
Turning usage telemetry into expansion motions before the customer asks
Expansion underperforms because the evidence for it is real but scattered. Feature adoption gaps sit in the product telemetry, unmet needs sit in support themes, and organisational change sits in nobody’s system at all. Account managers are asked to synthesise all three from memory during a quarterly review, so expansion becomes either a generic campaign or a reaction to something the customer asked for unprompted. The accounts that would have bought more are not identified late — they are not identified at all. The same fragmentation hides the opposite signal: teams occasionally pitch an upsell into an account whose usage has been declining for two quarters, which costs more than the deal was worth.
The agents here separate detection from action and keep a human on the second. Upsell Prioritization takes a usage export and ranks accounts by expansion potential with the segments and signals behind each ranking, while Product Fit Signals reads customer behaviour for what they need next and explicitly separates a real signal from a coincidence before anyone acts on it. Churn Signal Detection runs the risk side of the same data and flags which apparent churn signals are actually an expansion opening in disguise. Where an offer follows, Offer Personalization builds two or three bundles with what is in each, what it costs and who inside the account it targets. Nothing reaches the customer unreviewed: Upsell Proposal Routing sends the proposal to the right approver with the account’s health in view, so an expansion into a struggling account requires someone to say so out loud.
What this moves
- Expansion revenue
- Whitespace is identified from usage patterns rather than from an account manager's recollection, so more of the expansion opportunities that already exist get worked.
- Net revenue retention
- Churn signals and expansion signals are read from the same data, so an account is not sold into while it is quietly failing.
- Time from signal to conversation
- Behavioural signals are evaluated continuously instead of at a quarterly account review, which is where most of the delay currently sits.
Sales
How AI agents handle account growth
Drawn from the 12 agents above — what they require, how they run, and what comes back.
What they need
- Account health export
- Detection settings
- Customer base export
- Segmentation settings
- The inquiry
- Customer profiles
- What each field is for
- Customer message
What comes back
- Base health
- Accounts by churn risk
- Which signals are firing
- Act on these
- Interventions
- Segments
- Which customer is in which segment
- Motion per segment
How they run
- Run on demand
- 9
- Triggered by an incoming message
- 2
- Runs on a schedule
- 1
- Steps per run
- 2–4
- Credits per run
- 5–6
- Use a knowledge base
- 2
Where account growth fits in sales
Most of a rep’s day goes on looking things up, updating records and writing follow-ups. These agents do that part, so the hours left over go into conversations with buyers.
Next Step
Deploying account growth agents
These run as-is against the inputs listed above. Most deployments adapt one — a different source system, a different tolerance, a different approval path. The first call establishes which.