Building study tools has taught me one thing: students don't need another chatbot. They need a workflow that takes them from an assignment prompt to a finished, reviewable draft.
That's the idea behind Verla AI, an AI academic assistant I've been working on for university and college students. Here's how the pieces fit together.
The workflow
1. Draft with context. Instead of dumping a generic essay, Verla's AI essay writer works from the assignment requirements and academic context you provide — essay type, topic, sources you're working from — so the first draft is structured around the actual task.
2. Support every assignment type. Beyond essays, the same workflow covers research papers, literature reviews, lab reports, case studies, presentations, and coding or data-analysis assignments.
3. Review before you submit. Two tools handle this side: an AI detector that flags AI-generated content in a draft, and an AI humanizer that reworks AI-assisted text for readability, sentence flow, and natural expression while keeping the original meaning.
Why detection and humanizing matter
Most students already use AI somewhere in their process. The problem isn't using it — it's submitting text that reads like a machine wrote it, with no opportunity to review what's actually going out. Pairing generation with a detector and a humanizer closes that loop: generate, check, refine, then own the result.
What's next
I'm iterating on the research side (source organization for longer papers) and the presentation maker. If you're a student or you build for education, I'd genuinely like feedback: what does your current essay/thesis workflow look like, and where does it break down?
Verla is web-based and subscription-based, starting at $2.99: verla.io
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