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CASE STUDY · Media

Generative AI Content Pipeline for a Media Company

Published November 2026

The Problem

A media company wanted an AI pipeline that generates, fact-checks and formats articles from structured data while maintaining its editorial standards.

Architecture & Approach

We created an AI-powered editorial pipeline that generates, fact-checks and formats articles from structured data.

Outcome: content output increased 5x while editorial standards were maintained.

How we would build it in 2026

If we built this today, we would use Claude Opus 5.5 to draft articles from the structured data, hybrid search with reranking to check facts against approved sources, and LangGraph to run the generate, fact-check and format steps. This is our current stack, not the one this project used. Typical delivery: a 2-6 week pilot, then 6-12 weeks to production.

See how we deliver generative AI content pipelines.

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