Most business software politely waits until the customer interaction is over. Then it summarizes, files, nudges, scores, tags, and asks someone to clean up the mess. That is useful. It is also late.
For phone-heavy businesses, the call is the work surface. A caller is describing the issue, confirming an address, asking whether someone can come today, mentioning a warranty, and deciding whether they trust the business enough to stay on the line. If AI only shows up after hang-up, it misses the highest-leverage minute.
The live call is where context expires fastest
A live call has a strange half-life. Information is valuable for a few seconds, then it becomes archaeology. The address is useful when the agent is deciding which location record to open. The service history is useful when the caller says “same problem as last time.” The price boundary is useful before someone accidentally overpromises.
That is why is built around live guidance, not just after-call cleanup. The goal is simple: hear what matters, surface the relevant context, and help the person on the phone finish the work without turning them into a data-entry clerk.
The infrastructure is finally ready
This used to be hard because ordinary phone calls were opaque. Now tools like Twilio Media Streams docs can stream call audio to software in real time, and newer realtime model interfaces are built for low-latency speech and audio workflows. The OpenAI Realtime API docs are part of that larger shift.
The interesting product question is not “can an AI listen to a call?” It is “what should it do while listening?” Our answer: stay quiet until it can make the human better. Fill the checklist. Pull the right customer history. Warn on risky statements. Suggest the next question. Draft the work record. Do the boring parts before the agent has to ask.
After-call notes are table stakes
A summary after the call is helpful, but it cannot rescue a missed appointment slot, a forgotten address confirmation, or a caller who needed reassurance in the moment. Real-time AI should not replace the operator. It should give them the kind of context a great dispatcher, trainer, and operations manager would whisper if they could listen to every call at once.
That is the product line for us: AI that works during the call, in the same tempo as the business.
Sources worth reading: Twilio Media Streams docs and OpenAI Realtime API docs.