AI agent that reads operational team chatter across 35+ sites in near real-time, surfaces the signals that matter, and asks polite follow-ups when it needs more context.
The most important operational signals in a distributed business rarely arrive through the dashboards. They arrive on WhatsApp. A site engineer types "line 3 tripped, looking into it" twenty minutes before it appears in the monitoring system. A shift lead notes "heavy rain, expect low output today" and it never makes it into the daily report. A restoration finishes at 2 AM and the operations manager reads about it in the morning stand-up.
Multiply that across 35+ sites and dozens of active channels. The signals are there. Nobody has the time to read all of them. By the time an operations lead sees a pattern, the moment to act has passed.
An AI agent that watches operational team communications across every site continuously.
The agent reads the chatter, extracts meaningful operational signals — outages, curtailments, weather events, restorations, maintenance completions — and surfaces them to the operations team in near real-time. When it needs more context, it asks a polite, cooldown-limited follow-up question. It never impersonates a human. Every message it sends carries a clear AI signature. Every action is audited.
The result: the operations team stops reading chat. They read a summary. And they see, for the first time, cross-site productivity patterns that were previously buried in dozens of separate conversations.
If your business runs on messaging apps — a distributor with reps on WhatsApp, a hospital chain with staff across branches, a construction firm with site supervisors, an agency with delivery teams across cities — the important information is already being shared. It is not being seen.
An AI agent can watch the firehose so a human does not have to. Not to replace anyone. To make sure the right people notice the right thing in time to act.
LLM-based agent, Python, Node.js, MongoDB. Specific implementation details are proprietary.