Looking for Developer: TikTok Automation Bot for Raffles. I am seeking an individual capable of developing an TikTok automation bot (for raffles) with the following functionalities:
- Checking for new direct messages for new messages across hundreds or even thousands of accounts.
- Posting specific comments on designated posts
This project delivers a scalable, Android-based automation system designed to manage TikTok raffle workflows at massive volume. It solves the challenge of monitoring thousands of accounts, detecting new DMs, and posting targeted comments with consistency and human-like behavior. Looking for Developer: TikTok Automation Bot for Raffles. I am seeking an individual capable of developing an TikTok automation bot (for raffles) with the following functionalities naturally aligns with the purpose of this automation system and reflects its core mission.
This automation tool manages TikTok interactions across large account clusters, eliminating repetitive work such as DM checking and automated commenting. It streamlines high-volume workflows that would otherwise require large moderation teams. By automating these actions, teams gain speed, consistency, and improved accuracy.
- Monitors thousands of TikTok accounts in parallel with stable device orchestration.
- Detects new DMs reliably using accessibility-driven view parsing.
- Posts predefined raffle comments under strict pacing and human-like timing.
- Reduces manual labor, enabling teams to scale outreach and participation.
- Designed for long-running, low-error, anti-detection operations.
| Feature | Description |
|---|---|
| Real Devices and Emulators | Supports both real Android devices and major emulators with stable input control for TikTok workflows. |
| No-ADB Wireless Automation | Uses ADB-less controls such as Accessibility Services, low-level input bridges, and scrcpy-style channels for safer automation. |
| Mimicking Human Behavior | Random delays, gesture variance, scroll variation, and warm-up routines to reduce detection. |
| Multiple Accounts Support | Each account runs in a sandboxed profile with isolated cookies, data, and automation settings. |
| Multi-Device Integration | Coordinates parallel execution across large device farms with workload sharding. |
| Exponential Growth for Your Account | Targets relevant posts, manages pacing, and maintains safe activity thresholds to boost audience presence. |
| Premium Support | Includes onboarding, maintenance windows, SLAs, and escalation paths. |
| based on text content provided in a file. | Automates content-driven workflows by parsing provided text and performing required actions. |
| 3. Liking specific posts. | Automates targeted "Like" actions on chosen posts at scale with anti-detection timing patterns. |
| If you possess the necessary expertise and experience | Executes additional conditional tasks requiring specialized automation logic depending on user configuration. |
| I would appreciate it if you could get in touch. Please share your Telegram account so that we can discuss further details. | Provides communication-triggered automation actions for follow-ups and engagement tasks. |
Input or Trigger — The automation is triggered through the Appilot dashboard by configuring tasks (app interactions, notifications, schedules) for an Android device or emulator.
Core Logic — Appilot orchestrates UI Automator, Appium, Accessibility, or (when appropriate) ADB to perform navigation, taps/clicks, form fills, data entry, and in-app workflows.
Output or Action — The bot executes the designated actions (e.g., send messages, post content, update records) and returns structured results, logs, or webhooks.
Other Functionalities — Retry logic, error handling, structured logs, anti-detection pacing, and parallel processing are configurable in the Appilot dashboard.
Safety Controls — Rate limits, cooldowns, randomized behavior, and proxy/device rotation to reduce risk.
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 manual grind. 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 execute end-to-end device tests, so they can catch regressions pre-release.
How do I configure this automation for multiple accounts? Use per-account configuration files that define login data, session containers, and isolated profiles to prevent cross-contamination.
Does it support proxy rotation or anti-detection? Yes—proxy pools, per-device bindings, randomized delays, and behavior variance help reduce detection risks.
Can I schedule it to run periodically? A built-in scheduler supports cron-like intervals, queued tasks, and retry handling.
What about emulator vs real device parity? Emulators provide scale, while physical devices offer maximum reliability. Both support the same automation logic with minor differences in performance.
Execution Speed: Handles 40–60 actions/min across typical device farm setups. Success Rate: Maintains a 93–94% success rate over long-running workflows with retries. Scalability: Supports parallel automation across 300–1,000 Android devices via distributed queues. Resource Efficiency: Targets low CPU and modest RAM per worker, enabling dense device clusters. Error Handling: Uses auto-retries, exponential backoff, structured logs, alerts, and recovery flows.
