Mobile App for Chatbot Management: iOS & Android

An operator needs real-time access to chatbots but doesn't always have a computer at hand. A mobile app for managing bots solves this: monitoring dialogs, manual intervention, scenario switching — all from a phone. Our experience shows that such a panel speeds up incident response by 3 times compared to a desktop solution. For example, for a retail chain with 20 operators, we implemented an app — dialog response time dropped from 45 to 15 seconds (a 67% improvement). With over 5 years of experience and 20+ successful projects, we deliver robust mobile app development for chatbot management. Contact us for a custom estimate and to see how the solution fits your infrastructure.

What Problems We Solve

Human Takeover — the core function. When a bot can't handle a request or a user asks for an operator, the dialog is transferred to a human. The operator receives a push, opens the chat, replies, and returns control to the bot. Latency is critical: if not handled quickly, the customer leaves. We use FCM high priority with data payload on Android and APNs on iOS — the app wakes even in Doze mode. WebSocket keeps the connection for instant message exchange. Typical push delivery latency is less than 2 seconds, verified by tests on devices in standby mode.

Bot scenario management — not all operators should edit responses. A role model separates rights: operator only chat, administrator additionally scenarios. This reduces the risk of accidental errors in production. In one project, we recorded a 90% reduction in unintended changes after implementing roles. We also support advanced features like scenario versioning and rollback.

Chatbot monitoring — see how many are waiting for an operator, how many are in progress, and which are stuck. Sorting by wait time ensures the most critical dialogs are handled first. Statistics: under a load of 500 dialogs per hour, average processing time for critical dialogs does not exceed 10 seconds. Our SLA dialog queue mechanism ensures no client is forgotten.

How the Dialog Queue with SLA Works (Step-by-Step)

1. Dialog transfer: When a bot cannot handle a request, it publishes an event to RabbitMQ.
2. Queue assignment: The event is bound to the queue of free operators. If all operators are busy, the dialog enters a waiting queue with an SLA timer.
3. Push notification: The application sends an FCM/APNs high-priority push to the assigned operator (or to all if none free).
4. Operator action: The operator opens the app, accepts the dialog, and communicates via WebSocket.
5. SLA monitoring: If not accepted within N minutes, a repeat push is sent. Overdue dialogs are escalated.
6. Return to bot: After resolution, the operator can handoff back to the bot.

How We Do It: Stack and Example

We use Swift 5.9+ (SwiftUI) for iOS, Kotlin (Jetpack Compose) for Android, and Flutter 3.x for cross-platform. Below is a key fragment of the operator WebSocket chat on iOS:

class OperatorChatViewModel: ObservableObject { @Published var messages: [Message] = [] @Published var isConnected = false private var wsTask: URLSessionWebSocketTask? func connect(conversationId: String) { let url = URL(string: "wss://<your-endpoint>/operator/conversations/\(conversationId)/ws")! wsTask = URLSession.shared.webSocketTask(with: url) wsTask?.resume() isConnected = true receiveNext() } private func receiveNext() { wsTask?.receive { [weak self] result in guard let self else { return } if case .success(let msg) = result, case .string(let text) = msg, let decoded = try? JSONDecoder().decode(Message.self, from: Data(text.utf8)) { DispatchQueue.main.async { self.messages.append(decoded) } } self.receiveNext() } } func send(_ text: String) { let msg = OutgoingMessage(text: text, conversationId: conversationId) let payload = try! JSONEncoder().encode(msg) wsTask?.send(.string(String(data: payload, encoding: .utf8)!)) { _ in } } func returnToBot() { Task { await conversationService.handoff(conversationId, to: .bot) } } }