Darshan Rubber Industries manufactures industrial rubber components — gaskets, seals, moulded and extruded parts — for domestic B2B buyers and export markets. Despite a rich product catalogue, their written presence lagged far behind their factory's actual range.
Pcnet Infotech deployed Prompt2Publish — a fully serverless generative AI content pipeline on Amazon Bedrock — turning Darshan Rubber's datasheet library into the raw material for their entire content estate.
Datasheet rows exported as CSV and dropped into S3 ingest/. S3 event notifications fan each row into the Lambda generator. 300+ SKU backlog cleared in days of unattended runs at a fraction of a cent per description.
A tone guide for international B2B procurement engineers rides inside every prompt. A banned-superlatives list keeps copy factual and professional. One template governs structure — website and marketplace listings finally match.
Specifications are injected verbatim from SKU master data into every prompt. The system prompt forbids inventing or altering any rating, standard, or test value. Engineers verify specs — they no longer write paragraphs.
The application_note template targets one sector at a time — automotive sealing, pharma-grade gaskets, infrastructure joints. Steady cadence builds a long-tail keyword library that listings alone cannot capture.
Exhibition briefs batch-generate product one-pagers and booth social posts from the same grounded templates. Trade-fair preparation compresses from 2–3 weeks of scramble to 2–3 days of review and assembly.
Batch path: SKU datasheet CSV → S3 ingest/ → S3 event notification → Lambda → Bedrock → S3 generated/
Search: Marketing team → Amazon Q Business → indexed content library
"Three hundred products, and until now most of them had one-line descriptions. Prompt2Publish turned our datasheets into consistent, export-ready copy across the website and marketplace listings — our engineers now verify specifications instead of writing paragraphs." — Managing Partner, Darshan Rubber Industries
| AWS Service | Purpose | Configuration |
|---|---|---|
| API Gateway | Secure ingress | REST API; IAM SigV4; HTTPS; 10 rps burst |
| AWS Lambda | Content generation | Python 3.11; 512 MB; 60s timeout; concurrency 1 |
| Amazon Bedrock | LLM inference | Claude 3 Haiku; on-demand; temp 0.3–0.7 |
| Amazon S3 | Templates & content | SSE encryption; 90-day lifecycle on drafts/ |
| Amazon Q Business | Content search | Web experience; 1 Pro user (~$20/mo) |
| CloudWatch | Logs & metrics | 30-day retention; latency, error, token alarms |
| CloudTrail | API audit | Full Bedrock, S3, Lambda, API Gateway logging |
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