AI-Driven WhatsApp-Style Test Automation

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@maximg10

⭐Hello, I’m ready to assist you right away!⭐ I believe I’d be a great fit for your project since I have extensive experience in test automation, AI/ML, and software architecture. My approach will leverage on-premise frameworks like TensorFlow to develop a solution that learns from UI flows and user interactions to generate structured test cases for your WhatsApp-style application. This will ensure seamless testing without the need for cloud services. With my technical expertise, I will deliver a repeatable pipeline that produces executable test scripts for Android and iOS builds using Appium or Selenium. This solution will enable you to run the entire workflow offline on macOS, meeting your project requirements effectively. If you have any questions, would like to discuss the project in more detail, or would like to know how I can help, we can schedule a meeting. Thank you. Maxim

@AZTURK1

Hi there, I understand you need an on‑prem AI pipeline that ingests observable UI flows from a closed-source WhatsApp‑style app and emits replayable E2E tests for Android/iOS. I’m confident I can deliver a reproducible, offline solution using PyTorch/TensorFlow and Appium/Selenium. - Deliver a repeatable pipeline (capture → model → test case generator) that learns from recorded sessions - Deliver runnable test scripts (Appium-based cross‑platform) and Dockerized local training/runtime - Deliver setup instructions, sample data, retraining guide and a brief report with model logic and coverage metrics Skills: ✅ Software Architecture ✅ Python ✅ Machine Learning (ML) ✅ Test Automation ✅ Appium / Selenium ✅ Android and iOS Certificates: ✅ Microsoft® Certified: MCSA | MCSE | MCT ✅ cPanel® & WHM Certified CWSA-2 I can start immediately and deliver a working prototype within the agreed timeline. Which high-level user journey would you like me to implement first (text chat, voice call flow, or media sharing), and can you provide one sample captured session (screen recording + interaction log) for that journey? Best regards,

@johnallenvillan1

Hi, I'm excited about the AI-Driven WhatsApp-Style Test Automation project. With my expertise in Android, Python, and Machine Learning, I'll design a local machine solution using TensorFlow to infer test intent and generate executable test scripts for Appium. The pipeline will learn from sessions, produce structured test cases, and provide setup instructions for easy extension.

@larsenm2020

hi i have done similar project in past i can do this project have chat with me it will be worth your time i have done similar projects in past thank you

@brayanstiven5

Hi, there, I have vast experience in Test Automation, Software Architecture, Python, and Machine Learning. My proficiency in creating automated test cases aligns perfectly with your project requirements. Leveraging TensorFlow, PyTorch, or other local libraries, I will develop an AI-driven solution to generate end-to-end test cases for your WhatsApp-style application solely on a local machine.✅ Utilizing AI/ML techniques, I will analyze UI flows and interactions to infer test intent and produce executable test scripts for Appium or Selenium.✅ The deliverables will include a repeatable pipeline, setup instructions, and a detailed report on the model's logic and coverage metrics, empowering you to extend the suite independently.✅ I commit to ensuring that the generated tests accurately replicate high-level scenarios on the latest Android and iOS builds, enabling seamless offline execution on macOS.✅ I look forward to working with you. Best Regards. Brayan

@amaank66

Hello, This is a true AI automation problem—not simple test scripting—and it’s exactly the kind of system we design. You’re looking for a fully local, ML-driven pipeline that learns from UI interactions and generates executable end-to-end tests, and that’s achievable with a clean on-prem architecture. We propose a 100% offline solution using PyTorch/TensorFlow with Appium + Selenium for execution. Proposed System • UI/session capture ingestion • ML-based intent inference from user flows • Sequence modeling of journeys & transitions • Test intent abstraction layer • Automatic structured test generation • Script emitter (Appium/Selenium compatible) Deliverables • Local training + inference pipeline (code + model) • Repeatable workflow for learning from sessions • Sample datasets + retraining structure • Executable test scripts for Android & iOS • Setup documentation (macOS compatible) • Technical report: model logic, coverage, extensibility Assurances • Fully offline execution • No cloud dependencies • Reproducible training/testing • Scalable for new journeys • Deterministic, replayable test outputs This will be delivered as a true AI-based test generation framework, not rule-based automation. If you want a serious engineering solution rather than scripts, I’m ready to design the pipeline and milestones. Best regards, Amaan Khan P. CUBEMOONS PVT LTD.

@amadorjay

Hello, I will create an end-to-end testing solution for your WhatsApp-like application. This will involve generating executable test cases based on high-level user journeys. I have extensive experience in building automated testing frameworks. I’ve successfully implemented similar solutions for messaging apps and media sharing platforms, ensuring high reliability and coverage. **Implementation Approach:** - **Pipeline Architecture:** Establish a local pipeline using TensorFlow or PyTorch for model training and test case generation. - **UI Flow Ingestion:** Capture observable UI interactions and user flows for analysis. - **AI/ML Techniques:** Use machine learning to infer user intent and generate structured test cases. - **Output Execution:** Integrate with Appium or Selenium for executing the generated tests. - **Documentation:** Provide setup instructions and sample data for retraining or extending the test suite. **Key Questions:** - What specific user journeys do you want to prioritize for initial test case generation? - Are there any tools or frameworks you prefer for the execution of the tests? - How will you handle versioning for the Android and iOS builds during testing? I'm ready to start immediately. Let's ensure your testing pipeline is robust and effective.

@vasylklymiu

Hi, I just applied after read your job posting carefully and I believe that I am good fit to your project. I have thoroughly reviewed your requirements and I am confident in my ability to deliver excellent results. I'm a serious bidder. I will satisfy you with my high skills! I am an expert which have 8+ years of experience on Java, Python, Android, Software Architecture, Test Automation, Machine Learning (ML), Selenium, Automation I am looking forward to meet you to discuss the further detail about this project. Looking forward to hearing from you. Thank You

@cindyviorinar

Hi, I’ve read your brief and I’m confident I can build an on‑prem AI pipeline that observes UI flows for your WhatsApp‑style app and emits replayable end‑to‑end tests for Appium/Selenium. I’ll use PyTorch/TensorFlow for local model training, a session‑capture layer to convert UI traces into embeddings, and a rule‑guided intent inferencer to produce structured test cases (playable via Appium for Android/iOS). I also bring practical backend experience, REST APIs, service layers, DB interactions and refactoring, to ensure the test artifacts integrate cleanly with CI and logging. Next step: I’ll prepare a proof‑of‑concept capture → model → script generator and share setup + sample data so you can retrain locally. What are the high‑priority user journeys (text, voice, media) you want automated first, and can you share a sample session capture format you already have? Sincerely, Cindy Viorina

@chiragpipal

As you aim to automate end-to-end test case generation for a WhatsApp-like app without access to its source code, my 5 years of experience in similar projects offsite make me a suitable candidate for this task. Leveraging on-premise frameworks like TensorFlow or PyTorch, I propose to develop a local machine-based solution that learns from user journeys to output actionable test scripts runnable on Appium or Selenium. My approach ensures the generation of structured test cases reproducing high-level scenarios on both Android and iOS builds. I guarantee a seamless setup process, comprehensive instructions, and the ability for you to enhance the test suite independently. Let's discuss how my AI/ML expertise can benefit your project further. Chirag Pipal Regards

@growwithgdp

✅ I’ll build an offline AI-driven pipeline (PyTorch + Python) that captures UI flows, learns patterns from sessions, and auto-generates structured E2E test cases executable via Appium (Android/iOS). ✅ Approach: screen capture + event logging → sequence modeling → test script generation (Python/Appium), ensuring reproducibility and extensibility. ✅ Deliver full local setup, retraining guide, and coverage report for scalable test automation.

@stanislavy9

Hope you are doing well! I understand you need an offline, end-to-end AI-driven test generation pipeline for a WhatsApp-like app with no source access, producing executable Appium/Selenium scripts for Android and iOS on macOS. Key challenges include learning intent from UI-only flows, handling cross-platform UI differences, avoiding cloud dependencies, and ensuring reproducibility. I address this with a local PyTorch-based sequence model trained on captured UI event streams (XML hierarchies + interaction logs), combined with a rule-guided intent classifier to map flows into structured test cases. I’ve built model-driven automation frameworks where session recordings were converted into reusable test scripts. In one project, dynamic UI element IDs caused unstable playback; I solved this using attribute-weighted element matching and visual anchors. Another issue was scenario drift after app updates; I implemented coverage metrics and retraining hooks with labeled journey templates to maintain stability across versions. You’ll receive: full offline pipeline (code + model), sample datasets, retraining guide, coverage report, and documented extension workflow. I am ready for you and waiting here. Thank you.

@danielboggs

Hi there, I’ve read your brief and I’m confident I can build an on‑prem pipeline that ingests observable UI sessions, learns intent with a local ML model, and emits replayable Appium/Selenium scripts for Android and iOS. I have solid hands‑on experience building backend services in Java/Spring Boot (REST APIs, service layers, DB integrations), and practical ML + automation work in Python (TensorFlow/PyTorch for on‑device models, data pipelines, and model serving). My approach: capture UI flows as structured events, train a sequence‑model to map flows to test intents, and generate executable test scripts via a template engine. I’ll provide a repeatable code+model repo, retraining instructions, sample datasets, and a short report covering model logic and coverage metrics. I’ll prioritize reproducibility on macOS and use only local libraries. Next step: I’ll need your detailed user journeys and a few session captures to prototype a first model within a short iteration. Can you provide three representative session captures (screen recordings or structured event logs) and confirm whether you prefer Appium or a specific mobile driver for replay on iOS and Android? Best regards, Daniel

@drtaimoor

Hello, this is an interesting challenge and fully feasible with an on-device AI-assisted test generation pipeline. I propose a local workflow that records UI sessions from the WhatsApp-like app (via Appium accessibility tree + screen capture), converts them into structured interaction graphs, and trains a lightweight sequence model (PyTorch) to infer intents and generate reusable end-to-end test cases. The system will output executable Appium/Selenium scripts (Android+iOS) with parameterized steps for text, media, and call flows. Everything runs offline on macOS (Python + PyTorch + OpenCV + Appium), with retraining supported from new session logs. Deliverables include the full pipeline, training data format, generated test suite, and a short report covering model logic, coverage metrics, and how to add new scenarios. I’ve built similar automation/AI pipelines for UI and device workflows and can tailor this to your app’s journeys once shared. Timeline ~2–3 weeks for a working MVP.

@Hemantt841

I was immediately drawn to your project requiring AI-driven test automation for a WhatsApp-style application with no access to the source code. With over 7 years of experience in software development, I specialize in leveraging AI and ML technologies to solve complex testing challenges, making me well-suited for this project. Here's how I plan to approach this project: - Utilize TensorFlow for deep learning capabilities to analyze UI flows and user interactions - Develop a custom model that infers test intent based on observed patterns - Generate structured test cases compatible with Appium and Selenium for cross-platform testing - Provide a repeatable pipeline for learning from captured sessions and extending the test suite - Deliver setup instructions and sample data for future retraining and scenario expansion In a recent project for a messaging app, I implemented a similar AI-driven test automation solution that significantly reduced manual testing efforts while improving test coverage. The outcome was a robust test suite that accurately replicated user interactions across different platforms. As I delve into this project, could you clarify if there are specific edge cases or scenarios you anticipate encountering that should be prioritized in the test automation process? Feel free to review my portfolio for relevant work samples.

@OwlWingDesigns

my strong command over Python provides me with an arsenal that includes frameworks such as TensorFlow and PyTorch which can run entirely on your local machine. This aligns perfectly with your requirement of running the solution offline without resorting to cloud services. Harnessing these frameworks, combined with my proficiency in automation, I'll create a repeatable pipeline comprising code and model that extracts intent from observable UI flows and user interactions and translates them into reliable, executable test scripts. Before moving on, I want to address one key aspect you mentioned - the ability to retrain or extend the suite independently. Rest assured, this won't be a concern when working with me. My approach always includes thorough documentation so that my clients aren't dependent on me for basic upkeep post-completion. Thus, alongside everything listed in the deliverables, I'll include detailed setup instructions and helpful samples for your future reference. Let's optimize your testing process together!

@Ankurhardia34

Hello, I’m Ankur, a freelance developer with a dedicated team of professionals. I read all your requirements for website and I assure you that I will provide high-quality work at the proper time. Additionally, we also provide you 3 months of support from our side. As a Full Stack Developer, I specialize in Web and App Development, boasting a portfolio of stunning projects with top-notch UI/UX design. My expertise spans Flutter (for both Android and iOS), PHP, and WordPress, and I bring over 7 years of experience to the table. Whether it’s websites, applications, or e-commerce platforms, I’ve got you covered. But I’m not limited to just coding. My skill set extends to graphic design and logo creation, offering you a one-stop solution for all your project needs. With a track record of over 500 completed projects, I am committed to delivering nothing short of excellence. My ultimate goal is your complete satisfaction. Thank you for considering me for your project. I’m ready to transform your vision into a reality that stands out in today’s competitive landscape. Best Regards, Ankur Hardiya

@giancarld3l

“If you want this done properly, this is the proposal to read.” I understand you need an automated solution to generate end-to-end test cases for a WhatsApp-like app without access to the source code, focusing on text messaging, voice calls, and media sharing. With 5 years of experience, I propose utilizing AI/ML techniques to analyze UI flows and interactions, creating executable test scripts for tools like Appium or Selenium. The solution will run locally, leveraging frameworks like TensorFlow or PyTorch. Deliverables include a self-sustaining pipeline, setup guidance, and a detailed model report. Let's discuss your project to provide guidance or explore working together. Kind regards, Giancarlo