// discipline 01 / 10 · ai-ml
AI & ML Engineering
RAG, agents, evals: production-grade, not chatbot hype.
AI is our default, not an add-on. We ship LLM-backed features that survive contact with real users: typed contracts, evals on every prompt change, deterministic fallbacks when models drift.
Stack: Anthropic, Gemini, pgvector, LangChain primitives where they earn their keep, plain SDK calls everywhere else. Every call traced, every response evaluated, every cost line-itemed.
// live demo
› How does Netsphere approach AI projects?
Pick a prompt above to stream a response token by token.
Pick a prompt and watch a typed RAG-style answer stream back token by token. The same engine streams on the home page.
// related work
What this looks like shipped.
- Bots & AI Live
CTWA Bot
WhatsApp AI sales bot: multi-provider AI (Groq + Gemini + OpenRouter)
- Node.js
- Groq
- Gemini
- Bots & AI In build
ProDocs WhatsApp Bot
Gemini-powered lead generation and demo booking on WhatsApp
- Node.js
- Gemini
- WhatsApp Cloud API
- Mobile In build
Zyno
AI-powered fitness iOS app, pixel-exact SwiftUI build
- SwiftUI
- iOS
- Fastify
// start here
Bring us the part of the roadmap that scares you.
Tell us what is blocking the launch. We scope it in two weeks, build it to production, and stay on call after it ships.