Aether
Next-Gen RAG & Cloud Intelligence
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Aether - Next-Gen RAG & Cloud Intelligence

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Deploy production-grade local knowledge retrieval or scale effortlessly into high-throughput cloud reasoning engines.

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It establishes your credentials, explains why you built it, and highlights the technical value to drive conversions to your Kreato checkout link.


📍 Pinned Maker Comment

Hey everyone! 👋 Nageshkumar here, maker of Aether OS Pro.


As a developer building AI MVPs, I found myself wasting dozens of hours on the exact same setup for every project: setting up vector databases, configuring schema migrations, handling document chunking, and wiring up semantic caching. Worse, hitting cloud LLMs on every single user prompt was burning API budget fast during testing.


I built Aether OS Pro to solve this once and for all with a zero-token-cost, local-first production stack.


🛠️ What’s inside the box:

  • Framework: Next.js 16 (App Router + Server Actions with React 19)

  • Database & Vector Engine: PostgreSQL + Prisma 7 with native 1024-dim pgvector support

  • Embeddings & AI: Pre-configured for Voyage AI embeddings (production) and local Ollama runtimes ($0 offline testing)

  • Performance Layer: Sub-millisecond in-memory semantic query cache to skip redundant LLM API calls

  • Monetization: Pre-configured Paddle billing modal + instant local setup

🎬 Watch the 6.5-min technical build & demo:



⚡ Get the full production codebase (.zip) via instant UPI checkout:



I'd love to hear your thoughts on the semantic caching approach or answer any questions about the Prisma 7 pgvector setup below!


— Nageshkumar Gunji


Maker, Aether OS Pro