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NPrep delivers adaptive learning to nursing students and professionals in India through a 1400-hour video library personalized by AI. The tech stack reveals a full ML infrastructure—PyTorch, TensorFlow, OpenAI API, LangChain, LlamaIndex, and vector DBs (Pinecone, Weaviate, Milvus)—built to power RAG pipelines for doubt resolution and reduce hallucinations in medical AI, a critical safety constraint. The hiring mix is sales and marketing-heavy (7 of 10 roles), paired with backend scaling challenges, indicating product-market fit in a competitive nursing prep segment and a pivot toward revenue growth.
Tech Stack 30 technologies
Core StackNode.js NestJS TypeScript PostgreSQL MongoDB Redis Datadog New Relic Adobe Photoshop Adobe Illustrator Canva Flutter Mixpanel Google Analytics Python PyTorch TensorFlow LangChain Pinecone Weaviate FastAPI Flask OpenAI API LlamaIndex Milvus YouTube
AdoptingLlama Mistral
What NPrep Is Building
◆Challenges
- Scaling to thousands of concurrent users
- Performance bottlenecks in backend services
- Gaps in nursing test prep
- Student retention
- Reducing hallucinations in medical ai
- Scaling ai for thousands of students
- Improving accuracy in medical education ai
▲Active Projects
- Real-time quizzing
- Complex analytics dashboards
- Integrating new payment gateways
- Youtube thumbnail design
- Social media visual assets
- Ai-driven assessment tools
- Student retention funnels
- Spaced repetition and active recall tools
- Intelligent learning layer
- Rag pipeline for doubt resolution
Hiring Activity
Steady10 roles · 4 in 30d
Department
Seniority
Company intelligence
