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We chose Next.js for NeuraVid’s frontend because it offers the best balance of performance, SEO optimization, and developer experience. Its hybrid rendering (SSR + SSG) ensures fast page loads, which is crucial for video-heavy applications. API routes and middleware simplify backend interactions, reducing the need for a separate API layer for lightweight tasks. Compared to Remix or traditional React SPA, Next.js provides better SEO capabilities, automatic code splitting, and built-in image optimization, making it the best choice for a fast, scalable, and user-friendly web experience.

When selecting a speech-to-text & audio intelligence provider for NeuraVid.io, we compared several options, including Deepgram, Rev AI, AWS Transcribe, and Whisper-based APIs. We ultimately chose AssemblyAI because of the following key advantages: superior transcription quality, multilingual & the best speaker diariaztion that we tested

We used Pinecone for fast, scalable vector search to power NeuraVid’s AI-driven video retrieval. Unlike traditional databases, Pinecone is optimized for vector searches (ANN - Approximate Nearest Neighbor). As NeuraVid processes huge volumes of video embeddings, Pinecone’s fully managed infrastructure scales automatically, handling billions of vectors efficiently & we don't have to worry about it.