Government · Grievance management automation
Complaints sit unassigned because no one owns the routing
Banao builds grievance management automation for government departments — structured intake, auto-classification by subject and department, rule-based routing to the officer on record, SLA clocks that start the moment a complaint arrives, and escalation triggers when a deadline is about to slip.
The system integrates with your existing case management or service platform. Complaints do not fall through gaps because a queue was unchecked on a public holiday.
What the grievance automation covers
Each element targets a specific failure mode in manual complaint handling — unassigned queues, missed SLAs, untraceable redressal, and supervisors who only see a problem after a citizen escalates to a higher office.
Structured intake across channels
Complaints arrive by web form, email, WhatsApp, and walk-in. The system normalises them into a single structured record at intake — subject, department, priority, and complainant identity — regardless of channel.
Auto-classification and department routing
A trained classifier reads the complaint text and assigns it to the correct department and officer category. Misrouted complaints — the most common cause of redressal delay — drop to near zero.
SLA tracking with escalation triggers
Each complaint category carries a configurable SLA. The system sends reminders as deadlines approach and auto-escalates to supervisors when a case goes overdue, without waiting for a citizen to call back.
Officer workload visibility
A dashboard shows pending caseload by officer, department, and complaint age. Supervisors reassign from an overloaded queue to an available one without a meeting.
Citizen status notifications
Acknowledgement, assignment confirmation, and redressal notice go out automatically. Citizens know their complaint is moving without calling the counter.
Audit trail and reporting
Every status change, routing decision, and officer action is logged with a timestamp. Monthly redressal reports generate from the same data — no manual compilation.
We run intake automation on our own 300-person operation
Banao operates a ~300-person engineering company on its own AI before any client sees it. InterviewGod screens our own engineering hires — an intake and classification problem at volume. Vikaas runs our own demand-generation pipeline end to end.
We are not describing intake automation from the outside. We operate a version of it ourselves, which means the failure modes in routing and SLA tracking are ones we have already found in our own system rather than in yours.
- InterviewGodScreens Banao's own engineering hires — intake, classification, and routing at scale.
- VikaasRuns Banao's own outbound pipeline from intake to conversion, end to end.
When grievance automation is not the right first move
Not every complaint backlog is an AI problem. We name the cases where automation would add a layer without fixing the underlying issue:
- No consistent category scheme: if complaints are currently freeform with no agreed subject taxonomy, the first work is defining categories with your officers — the classifier needs a stable target.
- Fewer than a few dozen complaints per day: at low volume, a shared inbox with clear ownership rules often costs less and is faster to change when policy shifts.
- Redressal blocked by process, not routing: if complaints arrive correctly but sit because approvals or field visits are the bottleneck, automation moves the queue forward by one step and stalls at the next.
How we start — fixed-price, no commitment to a build
We map your complaint volume, current routing steps, and SLA breach rate before quoting anything. That mapping is yours to keep.
- AI Discovery Sprint2 weeks · fixed price
We audit a sample of your complaint records, map current routing logic and SLA targets, and hand back a classification feasibility assessment and implementation scope. If you proceed, the Sprint fee is credited against the build.
- Build
Intake normalisation, classifier training, routing rules, SLA engine, and officer dashboard — built to integrate with your existing case management or service platform, on-premise if your data-residency rules require it.
- Production & handover
Deployment with officer training, an audit log on every action, and a support window. Your team can adjust routing rules and SLA thresholds without a developer on every change.
Frequently asked questions
Our complaints come through multiple channels — web, email, walk-in. Can you handle all of them?
Yes. The intake layer normalises complaints from web forms, email, WhatsApp, and manually entered walk-in records into a single structured record. Adding a new channel later is a connector, not a rebuild.
How accurate is auto-classification before it can be trusted for routing?
That is exactly what the Discovery Sprint establishes on your actual complaint text. We will not quote a production build without a feasibility run on real data — accuracy on your category scheme, not a benchmark dataset.
Can SLA thresholds be different per complaint type or department?
Yes. SLA windows are configurable per category, department, and priority tier. Changes — when a policy update shifts a redressal deadline — are made in a configuration panel, not in code.
Does the system keep a human officer accountable for each decision?
Yes. The AI classifies and routes; a named officer accepts, acts on, and closes each complaint. The audit log records officer identity, action, and timestamp at every step — the accountability chain is stronger than a paper register.
Can it run inside our network without complaint data leaving our environment?
Yes. We deploy on-premise or in a sovereign government cloud. Citizen complaint data does not leave your environment for classification or routing — inference runs inside your perimeter.
Find out what it would take to clear your complaint backlog
Bring your current complaint volume and the departments involved. In 45 minutes we will tell you where the routing is breaking and what automation would change.
Book a 45-min scoping call