Context

AI agents that get smarter every week.

Context deploys agents inside your enterprise systems. They execute real workflows, learn from your team's corrections, and measurably improve. Work that takes days compresses to minutes.

Models are smart enough. They just don't know your company. Your procedures, your exceptions, your definition of quality. Context encodes all of it.

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Context
SaveRun
Workflows/Customer Success/Customer Save Package v3
Customer Save Package
v3 · edited 2w agoScope: Customer Success847 runs

Investigate customer churn risk, identify root cause across all systems, and prepare retention deliverables for CS team review.

Steps
1
Query Salesforce for all support tickets, NPS scores, and contract details for the target account.
salesforcecrm
2
Search Slack for internal threads mentioning the account.
Include engineering and support channels. Flag any threads mentioning "churn," "escalation," or "competitor."
slack
3
Pull product analytics: DAU, feature usage, login frequency.
Identify inflection points — any >20% change within a 2-week window.
analytics
4
Check billing system for disputes, late payments, or credit history.
billing
5
Search internal knowledge for prior incidents, escalations, or relevant context about this account.
knowledge
6
ifIf usage dropped significantly, run churn risk model and generate usage trend visualization.
Threshold: >30% DAU decline in any 4-week window.
compute
7
Compile findings into a save package: timeline, root cause, revenue impact, remediation plan.
output
8
Draft customer-facing email with acknowledgment, remediation steps, and proposed next meeting.
output
8 steps·6 integrations·~20s avg runtime·98.2% pass rate

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Week 2

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Week 3

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Week 4

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