tbuild.

Work

Systems we built, and what each one proves

Two of these you can open and use right now. The other two are private deployments, so we'll arrange a walkthrough instead.

01

Private AI setup

Clinic AI Receptionist

  • Go
  • Twilio Media Streams
  • On-device STT/TTS
  • LLM brain

Answers your clinic's calls end to end — greets, understands the caller, books, routes and escalates. Runs on a private voice stack, so it can live on your own hardware.

  • Cascaded pipeline: streaming telephony in, speech recognition, a language model holding the conversation, speech synthesis back down the line.
  • Speech runs on-device rather than through a third-party API — which is what makes a genuinely private deployment possible in the first place.
  • Books, routes and escalates on its own; everything touching caller data stays inside your perimeter.

02

Live

· reachable

Lead Intelligence

  • FastAPI
  • AgentScope
  • SSE streaming
  • Web discovery

Finds companies that match your ICP, enriches them from the open web, scores fit, and drafts the first outreach — with a research trail you can actually audit.

  • Discovery finds candidate companies on the open web; enrichment and scoring run as a pipeline of agents, not one long prompt.
  • Results stream to the browser as they land, so a research run is watchable instead of a spinner.
  • Every claim keeps its source, so a rep can check the reasoning before anything gets sent.

03

Live

· reachable

Voice AI with Domain Knowledge

  • Qwen3 ASR
  • Qwen 1.7B
  • Local embeddings
  • Qwen TTS

A voice agent that answers from your documents and nothing else. It says “I don't know” instead of guessing, and it runs fully on-device — no data leaves your network.

  • Two inputs, one gate: the agent answers only from the knowledge it was given.
  • Every model in the stack is local — recognition, reasoning, embeddings and speech — so it runs with no external API calls at all.
  • It says “I don't know” instead of inventing an answer, which is the behaviour that makes a voice agent safe to put in front of customers.

04

Private AI setup

Private AI Setup for Companies

  • On-prem or private cloud
  • Self-hosted models
  • Auth & isolation

We stand up agent infrastructure inside your perimeter: models, data, retrieval and access controls stay on your side of the wall, and you own the hardware and the bill.

  • We size the hardware to the workload, then deploy the models, retrieval layer and access controls inside your network.
  • You own the machines, the weights and the data. Nothing is metered by us.
  • Comes with a written cost comparison against running the same workload through a hosted API.

Your system won't look like any of these.

It shouldn't. These are the components we know how to make work — the shape comes from your problem.