Content generation at scale
Marketing teams cannot keep up with demand for localised, variant, on-brand content across channels. Quality suffers or production bottlenecks.
AI generates first-draft content from your brand playbook; human editors review, approve and publish, maintaining the brand voice at multiples of the current throughput.
- 01
The system is tuned on your brand playbook, tone of voice and past approved content.
- 02
Marketers describe the brief; the system produces multiple variants, per channel, per locale.
- 03
Editors review, edit and approve. Approved content feeds back into the training pool.
- 04
Compliance guardrails block claims or terms you have not pre-approved.
- 05
Performance data flows back in, so high-performing angles get surfaced for the next brief.
with 40 to 60 percent cost per piece reduction.
Ranges drawn from production deployments and public enterprise benchmarks. For a specific rupee or dollar figure tailored to your volume, use the calculator below.
Prerequisites for a clean deployment.
- A current brand playbook and tone-of-voice examples
- An editorial review workflow with named approvers
- A compliance list of restricted claims and terms
- A marketing ops owner for the workflow
Put your own numbers on it.
“At 1,000 documents a month and a loaded monthly cost of ₹1,50,000 per person, content generation at scale would typically save ₹9.8 L to ₹12 L a year.”
Range uses this use case’s typical automation rate against the baseline time per task for documents work, with your cost per person converted at 160 working hours a month.
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