A few weeks ago, I added a small AI voice assistant called Jarvis to my portfolio website. The setup...
Developer cut Groq API costs 70% via local intent matching, streamlined prompts, selective context—no model change needed. Tech signal: smart request architecture (intent layer, selective context) cuts token usage without performance loss or model switching.
A few weeks ago, I added a small AI voice assistant called Jarvis to my portfolio website.
The setup was intentionally simple: Groq handled text generation, while the browser’s Web Speech API handled speech-to-text and text-to-speech. Visitors could ask Jarvis about my work, projects, experience, or services, and it could also help them book a call.
It worked.
There was just one problem.
After about five minutes of fairly light testing, I had already burned through the Groq free-tier limit.
My pipeline was fast enough to interrupt people. Here is what I changed, what it cost, and the second...
My core is backend engineering Java/Spring, .NET, Python, cloud services. Over the last few months...
I built a voice assistant that controls 45 AI tools. I say "Hey Jarvis" and it executes. ...
Voice AI agents are magical until they start lagging. Suddenly my Groq-powered voice assistant...
How we gave Jarvis the ability to hear and speak — Phase 5 of the Jarvis AI Platform ...
When we talk about the power of Generative AI, we often focus entirely on the backend models. We...
