Instagram - Chatting Bot aside Fanzella AI DM Bot and Cupid Botcan anyone suggest a good chatting bot for instagram just like cupid and fazella that has low risk of getting banned?
This project sets up an Android-driven automation workflow that behaves like a smart Instagram chatting bot. It leans on controlled interactions, human-like pacing, and flexible device setups to reduce detection risks while handling repetitive DM tasks at scale. It’s designed for anyone looking for safer Instagram - Chatting Bot aside Fanzella AI DM Bot and Cupid Botcan anyone suggest a good chatting bot for instagram just like cupid and fazella that has low risk of getting banned? automation through reliable device orchestration.
This system automates Instagram messaging, interaction flows, and repetitive chat-based tasks on Android devices. It takes over the manual work of navigating inboxes, sending replies, and managing multiple accounts. The end result is smoother engagement, reduced workload, and a more consistent workflow for users or businesses managing conversations.
- Designed to imitate natural touch, scroll, and typing rhythms.
- Uses device-isolated sessions to avoid cross-contamination between accounts.
- Implements controlled message pacing tuned to reduce ban risks.
- Works seamlessly across emulators and physical devices.
- Flexible enough to integrate with proxy layers and routing rules.
| Feature | Description |
|---|---|
| Real Devices and Emulators | Works smoothly across physical phones and Android emulators, providing stable control and predictable behavior. |
| No-ADB Wireless Automation | Uses Accessibility services and low-level input pipelines to operate without needing ADB connections. |
| Mimicking Human Behavior | Introduces natural delays, variable gestures, random scrolls, and soft warm-up cycles to resemble a real user. |
| Multiple Accounts Support | Keeps each profile isolated through separate containers, cookies, and configuration slots. |
| Multi-Device Integration | Distributes workload across a farm of devices working in parallel. |
| Exponential Growth for Your Account | Applies controlled pacing and targeting to grow interactions safely. |
| Premium Support | Offers guided onboarding, fast-response SLAs, and maintenance coverage. |
| Proxy Routing | Enables device-level proxy assignment for safer account segmentation. |
| Message Templates Engine | Loads dynamic templates and randomized variations for safer DM interactions. |
| Task Scheduler | Runs tasks on intervals or triggers without constant supervision. |
Input or Trigger — Everything starts inside the Appilot dashboard by selecting a device and defining the actions you want automated—sending messages, handling replies, or navigating through inboxes.
Core Logic — Appilot coordinates UI Automator, Accessibility, Appium, or similar frameworks to move through the app, tap elements, enter text, and execute message flows.
Output or Action — The bot performs the requested DM actions and returns results, logs, and any captured event data.
Other Functionalities — It includes smart retry handling, structured logs, timing adjustments, and parallel execution on multiple devices.
Safety Controls — Built-in cooldowns, randomized touches, device rotations, and controlled message counts help reduce the chances of triggering platform restrictions.
Language: Kotlin, Java, JavaScript, Python Frameworks: Appium, UI Automator, Espresso, Robot Framework, Cucumber Tools: Appilot, Android Debug Bridge (ADB), Appium Inspector, Bluestacks, Nox Player, Scrcpy, Firebase Test Lab, MonkeyRunner, Accessibility Infrastructure: Dockerized device farms, Cloud emulators, Proxy networks, Parallel Device Execution, Task Queues, Real device farm
automation-bot/
├── src/
│ ├── main.py
│ ├── automation/
│ │ ├── tasks.py
│ │ ├── scheduler.py
│ │ └── utils/
│ │ ├── logger.py
│ │ ├── proxy_manager.py
│ │ └── config_loader.py
├── config/
│ ├── settings.yaml
│ ├── credentials.env
├── logs/
│ └── activity.log
├── output/
│ ├── results.json
│ └── report.csv
├── requirements.txt
└── README.md
Marketers use it to auto-send DMs to targeted audiences, so they can scale outreach without the repetitive workload. E-commerce teams use it to update listings across multiple stores, so they can keep catalogs consistent. Community managers use it to moderate and engage faster, so they can improve response times. QA engineers use it to run end-to-end tests across devices, so they can catch regressions earlier.
How do I configure this automation for multiple accounts? You define separate profiles, each with its own configuration folder, cookies, and device assignment to avoid overlap or mixed sessions.
Does it support proxy rotation or anti-detection? Yes—proxies can be bound per device, and every action is randomized, paced, and softened to avoid suspicious patterns.
Can I schedule it to run periodically? You can build recurring tasks using cron-like schedules inside the task scheduler with retries and fallbacks built in.
What about emulator vs real device parity? Both work well. Real devices are safer for sensitive accounts, while emulators help scale bulk tasks.
Execution Speed: Common flows average around 25–40 actions per minute across standard device clusters. Success Rate: Long-running job stability sits around 93–94% with retries enabled. Scalability: Supports deployment across 300–1,000 devices with sharded queues and horizontal workers. Resource Efficiency: Each worker typically uses moderate CPU and under 600–900 MB of RAM per device. Error Handling: Automatic retries, structured logs, delay strategies, and device recovery flows keep things stable.
