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What is this? A concrete recipe for wiring an AI customer-success agent against Salty’s CRM. The agent maintains an account health score, logs every touchpoint, surfaces at-risk accounts, and drives QBR prep — all over MCP or REST.

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The scenario

You sell SaaS to 50–500 customers. You can’t afford a CSM headcount per account. An LLM agent watches product usage signals, conversation transcripts, and ticket data; logs touchpoints; and when health drops, alerts you with the receipt of why. Salty is the system of record. Native objects map cleanly to the CS workflow.

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Data model

Salty objectYour concept
companyCustomer account
person (with primary_company_id)Stakeholder at that account (champion, exec sponsor, end user)
dealRenewal opportunity (one per account per renewal cycle)
activityTouchpoint — call, QBR, email, in-product nudge
noteFree-form context (call notes, exec change, competitive intel)
taskFollow-up items (REST/CLI only — no MCP write tool in v1)
custom_attributes on companyhealth_score, arr_cents, tier, last_qbr_at

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Set up the schema

Extend the company object once at start-of-life: 
curl -X POST $SALTY_API/schema/company/attributes \
  -H "Authorization: Bearer $SALTY_API_KEY" \
  -d '{"attribute_key":"health_score","display_name":"Health Score",
       "data_type":"number"}'

curl -X POST $SALTY_API/schema/company/attributes \
  -H "Authorization: Bearer $SALTY_API_KEY" \
  -d '{"attribute_key":"tier","display_name":"Tier","data_type":"enum",
       "enum_values":["starter","growth","enterprise"]}'

curl -X POST $SALTY_API/schema/company/attributes \
  -H "Authorization: Bearer $SALTY_API_KEY" \
  -d '{"attribute_key":"arr_cents","display_name":"ARR (cents)","data_type":"number"}'

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What the agent does on a typical week

TaskTool callsWhy
Pull the at-risk listsearch_companies with filter custom_attributes.health_score < 60Daily standup feed
Update health after weekly reviewupdate_company setting custom_attributes.health_scoreRecalculated from usage + sentiment
Log a CSM calllog_activity parent: company, type: csm_call, payload includes notes + durationAudit trail
Add a context note from Slackadd_note parent: companySurface non-meeting signal
Move renewal deal forwardupdate_deal stage transitionTrack $$$ at risk

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Driving it from Claude Desktop

Conversational prompt:
“Pull every company with health score below 70 and tell me who their primary contact is and when we last logged a touchpoint.”
Claude will:
  1. search_companies with {filter: {custom_attributes: {health_score: {lt: 70}}}} (the filter syntax)
  2. For each company, search_people with {filter: {primary_company_id: <id>}}
  3. search_activities with parent filters to find the most recent activity per company
  4. Surface a ranked table you can act on
The whole “QBR prep” workflow is one prompt instead of 40 minutes of dashboard clicks.

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React to churn signal via webhooks

When your usage-monitoring system pushes a low-engagement event, your agent can update Salty and Salty fires a webhook to your alert channel: 
curl -X POST $SALTY_API/webhook-endpoints \
  -H "Authorization: Bearer $SALTY_API_KEY" \
  -d '{
    "url": "https://hooks.slack.com/...",
    "subscribed_events": ["company.updated"]
  }'
Then your Slack receiver checks data.custom_attributes.health_score and pages you if it dropped below threshold. Salty does the persistence + signing + retry; you just react.

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Reporting

Get a CSV-ready dump of every company with health, ARR, and last activity: 
curl -G $SALTY_API/companies \
  -H "Authorization: Bearer $SALTY_API_KEY" \
  --data-urlencode "expand=primary_contact,latest_activity" \
  --data-urlencode "limit=100" > companies.json
The agent can run this nightly, transform to CSV, and post to your weekly dashboard.

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Volume guidance

A 100-account CS practice with weekly check-ins makes ~10,000 API calls/month (~25 calls per account per week). The Solo ($20/mo, 100k calls) plan has 10× headroom. Pro ($99/mo, 1M calls) if you have hundreds of accounts.