marketing_ops · finance · workflow
Carta increases AI search citations 7x with AirOps
Carta's editorial team operated without consistent content request processes, relied on highly manual regional production, and was slowed by complex review cycles, leaving little time for creative strategic work while also struggling to maintain brand consistency across a growing global operation.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Content request received
Content requests arrive through various processes without clear consistency.
Tools used
AirOpsBrand KitChatGPT
Outcome
Within the first few months, Carta achieved a 300% increase in content velocity from 5 to 20 pieces per quarter, over 60% time savings, a 75% citation rate on new pages created with AirOps, and an average of 3 days from publication to AI search citation.
What failed first
Carta experimented with ChatGPT and several other general-purpose AI engines before AirOps, but found them too rigid or impersonal for brand-consistent content creation.
Results
Time saved60%+
Volume7x
Grounding & classification
Source type: vendor customer story
26 fields verified against source quotes.
content generationpersonalizationknowledge basefailure mode describedhuman review describedmetric backednamed customerproduction runtime claimedtools describedworkflow describedfinancial servicesemployee productivitythroughput increasetime savedvendor customer storyback office opsmarketing opsai draft human approval