Many teams believe AI can generate text, but Evrone wanted something much more practical: an assistant capable of accelerating the entire content preparation process without replacing creative professionals.
Publishing several videos every week meant handling research, news monitoring, interview preparation, and long-form scripts. Manual workflows simply couldn't keep pace.
Instead of relying on one large language model, Evrone developed Screenwriter, an internal system where multiple AI models collaborate.
🔹 The workflow
1. Audience understanding
AI builds behavioral profiles instead of relying only on web analytics.
Every future topic is evaluated against audience interests.
2. Information filtering
Thousands of multilingual articles and news updates are analyzed.
Relevant stories receive automatic priority.
3. Script preparation
Selected topics become structured podcast or news scripts within minutes.
💡 Why multiple models?
Different models excel at different tasks.
- ✅ Information analysis
- ✅ Narrative organization
- ✅ Script writing
Using several providers also prevents production from stopping if one service introduces limitations or becomes unavailable.
📈 The outcome
Screenwriter dramatically reduced preparation time while lowering production costs. Teams could publish significantly more episodes without expanding editorial staff.
However, Evrone emphasizes an important principle:
AI supports creators—it does not replace them.
Editors and presenters still review every script, contribute industry expertise, and shape the final story.
For Evrone, the biggest innovation wasn't simply generating text. It was creating a scalable workflow where AI handles repetitive research and organization, allowing people to focus on creativity, expertise, and meaningful communication.
💡 Building an AI Content Pipeline: Lessons from Evrone's Screenwriter.
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