Last week a resident asked about Rose Music Center.
This week the agent knows.
Every call is scanned for gaps, the fix is drafted from your own sources, and staff approve it in two clicks. The knowledge base never gets stale.
From a live deployment
Every gap becomes the next fix
Real gaps flagged from production calls in Huber Heights, Ohio, one review cycle, with the drafted fixes the city approved.
How a gap gets fixed
Scan
Every completed call is checked for gaps: unanswered questions, missing transfers, processes that live only in someone's head.
Draft
The fix is drafted from your jurisdiction's own sources, with citations, even when the answer lives in a four-year-old PDF.
Approve
Staff review the gap and the drafted fix side by side, and approve in two clicks. Nothing changes without a person saying so.
Report
A weekly coverage report groups the issues by root cause and ranks them by residents affected: a handful of priorities, not a hundred alerts.
The gaps are found by call oversight, which audits every call automatically.
Continuous QA questions
Does the AI change its own knowledge base?
No, and that is deliberate. The system drafts recommendations; a person on your staff or ours approves every change before it takes effect, and each resolution is recorded. For government, human sign-off on what the AI is allowed to say is a feature, not a limitation.
Where do the drafted fixes come from?
From your jurisdiction's own sources: your website, your published documents, your event pages, your county partners' official sites. Draft fixes carry citations, and cited links are checked before they reach your review queue.
What does the weekly coverage report show?
The week's issues grouped by root cause rather than listed call by call: one recurring gap that touched five residents shows up as one prioritized recommendation, not five alerts. Recommendations are ranked by how many residents each gap affected, and your team controls the sensitivity of what makes the report.
How much staff time does this take?
The review is the two clicks: open the flagged gap, see the drafted fix and its source, approve. In Huber Heights, the gaps a staff member used to hunt for across departments now surface on their own with the fix already drafted.
What kinds of fixes come out of the loop?
New knowledge-base coverage (an undocumented fee, a venue the city does not operate), new transfer destinations (traffic tickets belong to the county court), and new text links (the signup form residents keep asking for). Whatever the calls show residents actually need.
How is this different from a vendor doing periodic reviews?
Cadence and coverage. A periodic review samples some calls occasionally; continuous QA scans every call as it happens and never stops. The knowledge base decays the moment hours change or an event ends; the loop catches the decay from the very first call it affects.
Not an AI receptionist
A receptionist bot answers one number. This runs every department’s line.
Running an entire government’s phones takes more than an AI receptionist. It takes five systems working together, and accountability.
The improvement loop
Continuous QA
Turns the flags into drafted fixes your staff approve in two clicks.
So a resident explains their issue once, gets a real answer in any language at any hour, and the city never has to grow the front desk.
See your own gaps surface
In a live demo we'll show the review queue from a real deployment, and what the first weeks of your own coverage loop would look like.
