AI Research Assistant
From raw idea to 230+ paying users in one sprint.
Overview
A founder in the academic and corporate research space came to us with a clear problem: research teams were spending hours manually reading, summarizing, and cross-referencing papers. They needed a product that could ingest PDFs, run AI analysis, and surface insights — all in a clean, shareable interface.
The Challenge
The hardest part wasn't the AI — it was the workflow. Users needed to upload multiple documents, run comparisons, and export structured summaries to Notion or email. We had to design a data model that made this feel effortless, not like running a command.
What We Built
We built a Next.js SaaS with Supabase for document storage and OpenAI for GPT-4-powered summarization and citation extraction. Each document gets processed asynchronously, results cached to avoid re-billing, and a clean dashboard shows everything at a glance. Stripe handles tiered subscriptions with a free trial.
The Outcome
The product launched on Day 7. Within two weeks, 40 beta users converted to paid. By Month 2, the founder had 230+ users and was using the MRR to fund a V2 sprint with us.
What was built
"I'd been planning this for 8 months. Existify shipped it in 7 days and it looked better than anything I'd imagined."
Tech Stack
Results
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