AI-Powered Data Pipelines
Agents that ingest, clean, enrich, and route data with LLM reasoning at every step. An analytics team at a logistics company automated 80% of their weekly report generation with Diaflow.
How it works
Customer story
An analytics team at a logistics company in Southeast Asia was manually assembling weekly operations reports from three different data sources. The process took 4-6 hours every Monday and was prone to errors when data formats changed upstream.
They built a Diaflow pipeline that ingests data from their APIs and databases, uses an LLM step to normalize and enrich records, deduplicates with configurable rules, and routes output to PostgreSQL. A second agent generates the weekly report from the cleaned data and posts it to Slack. The full pipeline runs in under 10 seconds.
"We didn't realize how much of our Monday mornings were going into data prep. Now the report is ready before anyone logs in. The team actually trusts it more because the LLM catches formatting issues our old script missed."
Head of Analytics, logistics data team, SEA
Key features
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