Marketing ops · Production

Gradial uses Claude to automate enterprise marketing campaign execution, cutting 300-hour workflows to under 10 hours

The problem

Enterprise marketing teams face 20-plus operational steps between a brief and a live campaign — including authoring, QA, asset tagging, and stakeholder approval chains across fragmented tools — stretching execution timelines to weeks, while existing software tools lack the workflow context needed to solve it.

Workflow diagram · grounded in source
1
Onboarding brand rules extraction
ai_action
“During customer onboarding, Claude processes brand guidelines, design system documentation, and component libraries to extract the structured rules that power downstream execution.”
2
Marketer assigns campaign task
trigger
“When a marketer assigns a task like building a landing page from a Figma file, executing a content update from a Jira ticket, or creating page variants for experimentation”
3
Orchestration engine routes subtasks
routing
“an orchestration engine that routes each task to the best-fit model for that customer's context”
4
Claude authors CMS content
ai_action
“Claude often handles the tasks requiring detailed instruction-following: authoring content into specific CMS components while respecting governance constraints and design system specifications”
5
Brand compliance and QA validation
validation
“Claude helps perform brand compliance checks, accessibility validation against WCAG 2.2, and content QA against customer-defined rules. Every output gets validated before it goes live.”
Reported outcome

Bulk component update operations that previously required 300+ hours can now be completed in less than 10 hours with perfect accuracy, campaign time-to-live improved by 90%+, and enterprise environments with highly custom CMS architectures that previously required heavy manual support are now within reach for agentic automation.

Reported metrics
Bulk component update time (before)300+ hours
Bulk component update time (after)less than 10 hours
Bulk component update accuracyperfect accuracy
Campaign time-to-live improvement90%+
Show all 7 reported metrics
bulk component update time (before)300+ hours
bulk component update time (after)less than 10 hours
bulk component update accuracyperfect accuracy
campaign time-to-live improvement90%+
content operations work automatablehundreds of hours of effort and QA
enterprise campaign workflow operational steps20-plus
evaluation tasks tested25
Reported stack
ClaudeOpusAWSAzureGCPFigmaJiraClaude CodeCowork
Source
https://www.anthropic.com/customers/gradial
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Bulk component update operations that previously required 300+ hours can now be completed in less than 10 hours with perfect accuracy, campaign time-to-live improved by 90%+, and enterprise environments with highly cu…

What tools did this team use?

Claude, Opus, AWS, Azure, GCP, Figma, Jira, Claude Code, Cowork.

What results were reported?

Bulk component update time (before): 300+ hours; Bulk component update time (after): less than 10 hours; Bulk component update accuracy: perfect accuracy; Campaign time-to-live improvement: 90%+ (source-reported, not independently verified).

How is this marketing ops AI workflow structured?

Onboarding brand rules extraction → Marketer assigns campaign task → Orchestration engine routes subtasks → Claude authors CMS content → Brand compliance and QA validation.

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