Customers

What people built on AvA

The engine is the product beneath the products. Here is what gets built when you hand it to someone with a business to run.

01

Homebridge.ai

Property technology

Runs its entire lead pipeline on AvA — every enquiry called, qualified and routed by voice agents, with campaign follow-up handled end to end.

The problem

Property enquiries arrive in bursts and go cold fast. A lead that waits until the next working morning for a call back has usually already spoken to somebody else. Staffing for the peaks means paying for the troughs, and asking a human team to make the same qualifying calls all day is how the quality of those calls quietly falls off.

What they built

  • Every inbound enquiry is called back automatically, within minutes of arriving, without anyone queuing it.
  • The agent qualifies on the call — budget, location, timeline, intent — instead of booking a human call to find out.
  • Qualified leads are handed to the right person with the transcript attached, so the first human conversation starts from what was already said.
  • Outbound campaigns run against segmented lists, at whatever hour the list is actually reachable.
  • Follow-up sequences continue across calls and messages until the contact responds or opts out, with no one maintaining a chase list.
Agentic callingLead automationCampaign automationJourneys
02

Vidya

Education

An AI tutor built on the AvA engine, giving students academic support by voice in their own language.

The problem

Good tutoring does not scale, and the students who most need it are usually furthest from it — often studying in a language the available material was never written in.

What they built

  • Voice-first tutoring across school subjects, from primary through to school-leaving level.
  • Conversations in the student’s own language rather than translated material.
  • Sessions that pick up where the last one ended instead of restarting cold.
Realtime APIMultilingual voiceKnowledge base

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