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Devendra Jangiddevendra.pro

Voice AI & Edge Hardware

Speech-driven systems that run on your own hardware

Voice is the easiest interface there is for people whose hands are busy — a warehouse, a shop counter, a workshop. I build speech systems on open-source models that run on your own machines, so there is no per-minute cloud bill and no recordings leaving your building.

What you end up with

  • Hands-free capture where typing is impractical
  • Speech models running on hardware you own, with no usage meter
  • Audio and transcripts that never leave your network
  • Low-cost devices doing real work on the shop floor
  • Works on a weak internet connection, or none at all
Is this you?

Signs you need this

If two or three of these sound familiar, it is probably worth a conversation.

  • Your staff have their hands full and typing is genuinely impractical
  • Cloud speech APIs would cost more than they save at your volume
  • Recordings of your operations must not leave your premises
  • Connectivity at the site is unreliable but the work still has to happen
  • You want smart devices doing real work rather than a novelty demo
Scope

What is actually delivered

Not a statement of intent — the concrete artefacts and outcomes you receive.

01

Self-hosted speech stack

Speech-to-text and text-to-speech running on open-source models — Whisper for listening, Piper for speaking, and a local language model where one is needed. Your servers, your data.

02

Edge devices

Low-cost single-board computers with a microphone and speaker, deployed where the work happens, talking to a central server over a documented protocol.

03

Real-time audio handling

Voice activity detection, streaming over websockets, wake-word handling and noise tolerance — the unglamorous engineering that decides whether a voice system is usable or infuriating.

04

Home and building automation

Devices, sensors and voice control tied into an automation hub, self-hosted on your own cloud VM rather than a vendor's subscription.

05

Deployment and monitoring

Containerised deployment, remote updates and health monitoring, so a device in another city can be looked after without a site visit.

Method

How the engagement runs

  1. 01

    Scope

    Work out honestly whether voice is genuinely better here than a screen or a scanner.

  2. 02

    Prototype

    One device, one flow, tested in the real room with the real background noise.

  3. 03

    Harden

    Handle accents, noise, dropped connections and the ways people actually speak.

  4. 04

    Deploy

    Roll out to more devices with central monitoring and remote updates.

Questions

Voice AI & Devices: common questions

Better than most people expect, but it has to be tested in your actual room rather than trusted from published figures. Microphone choice and placement usually matter more than which model is used, which is why prototyping happens on site.

Where this applies

Voice AI & Devices in your industry

The problems look different in each of these, so the way I approach them differs too.

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