0 to production in 6 weeks. Pilot-ready and investor-demo-ready - PromptID
PromptID is an AI-native EdTech platform for employers and universities. It examines learners by analysing the train of thought, not by rewarding memorisation. A proprietary algorithm drives the assessment engine.
What was the main challenge in this project?
The market moved mid-build and the timeline shrank by a month. Pilot conversations and investor demos sat on the calendar. LLM agnosticism, intuitive UX, production-grade from day one, none negotiable. The month had to come from scope, not quality.
What was your solution or approach?
The original Gantt had a final month of QA and testing. The market took that month, so we had to be production-ready earlier. The reflex move is to cut testing rigor. We cut feature scope instead. The production-quality bar held by squeezing the surface area, not the testing time. The investor demos and pilot conversations on the client's calendar got what they needed.
What was the outcome or impact for the client?
Timeline shrank by a month mid-build. We cut feature scope, not QA, and held the production bar. NestJS API with a BullMQ eval queue, NextJS frontend, LangChain so model swaps are config, Kubernetes autoscaling. Shipped pilot-ready and investor-demo-ready in six weeks, when the market needed it, not when the Gantt did.