The real-time AI space is moving fast. Exploring options for real-time, conversation-driven analytics and DB-backed interactions.
OpenAI’s revamped Realtime API, Google’s Flash 2.0 Experimental, and ElevenLabs’ Conversational AI are all raising the bar while driving down costs.
Built 𝐑𝐄𝐗-𝐑𝐓, a mobile-friendly app powered by OpenAI’s Realtime API. It connects to a PostgreSQL database with 1.5M cricket records—live, searchable, and fast. Using WebRTC, gpt-40-mini, and function calling. 𝐂𝐨𝐬𝐭𝐬 ~$𝟎.𝟎𝟓–$𝟎.𝟎𝟕 𝐩𝐞𝐫 𝐦𝐢𝐧𝐮𝐭𝐞. Fully customizable.
While the demo uses cricket data, it can support domains like finance, retail and beyond.
Performance: Solid, but not plug-and-play. Needs deep dives into event flows, WebRTC, and APIs. It's a code-and-build journey.
Last week, I shared 𝐑𝐄𝐗-𝐂 (cricket-odi.tigzig.com), built with Eleven Labs’ Realtime Voice Widget. Plug-and-play simplicity, excellent performance (~$0.20/min), but limited UI customization—unless you use their SDK.
The possibilities: Huge. Conversation-driven analytics, voice integrations, realtime DB backed conversations, scalable apps for enterprises.
Other tools to explore: Gemini 2.0 Flash Experimental, Eleven Labs, Hume AI and packaged ones like Vapi, Bland AI, Synthflow and others.
-----------------------------
Tech Details—Source Code
REX-RT is built with 𝐂𝐮𝐫𝐬𝐨𝐫 𝐀𝐈. Vanilla JS/HTML with CSS for mobile responsiveness, FastAPI for DB connectivity, and Flowise AI for LLM agents. Basic security is via domain whitelisting.
Most of my apps lean on React, but loving Vanilla JS for its raw power and speed to deploy—though it trades some polish for simplicity.
Source code, deployment guides and learning resources: rex.tigzig.com > Multi-tasker AI Apps > REX-RT > Help & Build Guides > Build It.
Main Repo: https://lnkd.in/gXKbXF7s
Caveat: This is a working prototype with a single agent (gpt-40-mini). Data is sourced from cricsheet.org' s experimental CSV section and isn’t independently validated.