Native AI Customer Support App

@Microlent

Hi, I've reviewed your requirements carefully. This is a highly specialized native application that combines telephony, on-device AI, offline speech processing, and knowledge-based question answering without relying on any cloud services. Our team can develop the application using native Android (Kotlin) with an architecture that integrates offline STT/TTS engines, local LLM inference, SQLite-based knowledge storage, call transcript management, and intelligent call escalation. The solution will be modular, making it straightforward to add more languages and extend the knowledge base in future releases while keeping all AI processing on the device. The application will include OTP authentication, multi-number management, offline knowledge search, bilingual English/Hindi conversations, configurable male/female voices, and sequential call forwarding when escalation is required. We'll also provide complete source code, technical documentation, build instructions, and a demonstration covering all acceptance criteria. One important question before we begin: is this application intended only for Android, or do you require feature parity on iOS as well? Also, are you aware that iOS imposes significant restrictions on call handling, which may limit implementation compared to Android? Looking forward to discussing your project. Rajesh

@kaustubhkpatil

As an experienced Mobile Phone Developer specializing in Android platforms, I am confident in my ability to tackle your project and deliver a high-quality app that meets every one of your requirements. My extensive background in Ai development, especially on-device ML and native telephony APIs, coupled with my proficiency in Kotlin/Java will ensure the success of your Native AI Customer Support App. Not only do I understand the significance of an efficient mobile app, but I also have a deep appreciation for clean, native codebases and local data storage. This means I can carefully structure your app using SQLite or similar technology to optimize performance and simplify future updates. Additionally, my fluency in Hindi is a bonus when implementing multilingual interaction into the application. Crucially, I am always result-oriented and up to date with the latest trends in mobile app development. If hired, I will ensure that all features of your app function seamlessly even in airplane mode, providing confirmation that no external services are used for any AI or voice-related functionalities. Aftercompletion, expect comprehensive hand-off deliverables including source code with build instructions and technical documentation detailing the models used and speech handling approach.

@jagratip3

Dear Hiring Manager, I have extensive experience in Android application development, on-device AI, telephony integration, and offline mobile solutions, and I can build a secure, native application that matches your requirements. The app will be developed in Kotlin with clean, modular architecture, supporting OTP login, multi-number management, local SQLite storage, offline knowledge base search, bilingual (English/Hindi) conversations, dual male/female TTS, and complete call transcript management. I'll implement robust call handling, automatic escalation to registered numbers, and ensure the architecture is ready for adding more languages. For AI inference, speech processing, and knowledge retrieval, I will use fully on-device models and engines, avoiding external AI or speech APIs as requested wherever supported by the target platform. I'll also provide complete source code, build documentation, and a demo covering all acceptance criteria. I am ready to start immediately and would be happy to discuss the best on-device architecture for this project. Best regards, JP

@mobasherreza10

As an AI enthusiast, developer, and a seasoned professional in mobile app development, I believe I bring the precise skillset needed to actualize your Native AI Customer Support App. My wide-ranging experiences in Flutter, Android, Kotlin and Swift give me a profound understanding of the native app development terrain. I am also skilled in deep learning frameworks such as TensorFlow and PyTorch which will be vital for implementing on-device ML capabilities. Moreover, your project's emphasis on robust telephony integration aligns squarely with my strong background in APIs and microservices, notably in using telephone APIs for speech and call handling. Given that your app is set to handle English and Hindi initially with plans to expand to more languages, it's worth noting that my familiarity with multi-lingual NLP frameworks such as LangChain and Hugging Face will be a great asset.

@anshuman5050

Your project perfectly matches my expertise in AI, on-device ML, and intelligent automation. I can build a native Android solution with offline AI inference, bilingual (English/Hindi) STT & TTS, local knowledge base, telephony integration, call escalation, and secure chat history—all with clean, scalable code. I'll use a modular architecture so future languages and features can be added easily. The solution will be well-documented, production-ready, and designed to meet your offline-first requirements. I'd love to discuss the implementation and get started.

@dushyant317

I can build a native on-device AI calling assistant with offline knowledge retrieval, multilingual speech interaction, local storage, and intelligent call-routing workflows. The solution will focus on secure local inference, seamless telephony handling, and scalable architecture while keeping all AI processing on-device without relying on external cloud APIs.

@fizaa170

Your concept is ambitious and technically challenging because it combines on-device AI, native telephony, offline speech processing, and real-time call handling without relying on any external APIs. The architecture will need to prioritize performance, memory optimization, and reliable offline inference from the start. I'd build this as a native Android application using **Kotlin**, **SQLite**, **TensorFlow Lite/ONNX Runtime** for on-device AI inference, offline **STT/TTS engines**, and Android's Telecom/ConnectionService APIs for call handling. The application will support OTP login, multilingual knowledge retrieval (English/Hindi), call transcripts, configurable male/female voices, and sequential call escalation while keeping all AI processing entirely on the device. One recommendation is to use a **Retrieval-Augmented Generation (RAG)** approach with an embedded vector database for the local knowledge base. This delivers faster and more accurate responses than searching plain text while remaining fully offline. **One question:** Will this application be deployed only on **Android devices** (where native call interception is possible), or do you also require **iOS support**, considering iOS heavily restricts third-party call handling and automatic call answering?

@sgwtechnology

Hello, Your project is ambitious and aligns well with my experience in native Android development, on-device AI, and telephony integration. I can build a fully offline-first solution where the knowledge base, speech processing, and AI inference run locally without relying on cloud AI services. The application will include: Native Android (Kotlin) architecture with clean, modular code OTP-based registration and multi-number management Local knowledge base (SQLite) with fast semantic search Offline STT/TTS supporting English and Hindi with selectable male/female voices Automatic call handling, conversation logging, and sequential call escalation Secure local storage and detailed technical documentation Before development, I recommend confirming device and OS constraints, as some call-answering and call-control capabilities depend on Android version, OEM restrictions, and whether the app is used as the device's default calling app. You'll receive complete source code, build instructions, deployment documentation, and a demo covering the required workflows. I’m ready to discuss the architecture and implementation plan in detail and begin development immediately.

@iterativeTech

As an AI and data specialist with a focus on developing intelligent systems and real-time insights, I'm uniquely positioned to tackle your project. With a deep understanding of both on-device ML and native telephony APIs, I can build the fully native mobile application you need to answer incoming calls, resolve queries using your built-in knowledge base, and even escalate to human support when necessary - all without the reliance on any external APIs, just like you've specified. My proven track record in building scalable, production-ready systems aligned with business objectives is a testament to my ability to deliver an app that meets your needs. Having worked extensively with AI/ML development and cloud data engineering – similar to what you require – I am experienced at leveraging AI for Voice solutions through technologies like n8n, Relevance AI, OpenAI, Voiceflow, Twilio, etc. In addition to my AI/ML expertise, my proficiency extends to Android development (Kotlin/Java) – ensuring clean, native codebases. My proficiency with Python will help in setting up SQLite local storage for your knowledge base and chat history. Rest assured, the deliverables include a brief technical document summarizing the on-device models, speech engines used, and the call handling approach adopted – a reflection of my commitment to transparency throughout the development process. Let's craft an impressive customer-support app together!

@erincguray

Greetings, I am Erinc. I am a Full stack developer knowledgeable in Python and .NET. I can help you with you need a fully native mobile application that can answer incoming phone calls on our main business number, speak to the caller in either a male or female voice, and resolve their questions from a built-in knowledge base no external APIs allowed at any stage. Looking forward to hear from you. Thanks for your consideration.

@Sajid293r

Hi there, I hope you’re doing well. I have reviewed your requirements and can develop this native AI-powered call assistant with on-device ML, offline knowledge base, multilingual voice interaction, OTP authentication, intelligent call routing, and seamless telephony integration. I’ll deliver clean, scalable code, complete documentation, and ensure all acceptance criteria are met with a reliable, production-ready solution.

@souvikbasu

Hi, I build native mobile apps with on-device AI, so your "no external APIs" requirement is exactly what I work within. How I'd deliver it: • Native app (Flutter or React Native) with OTP login, primary number + up to 4 additional numbers • First-time setup screen to capture your business overview and knowledge base • On-device speech: local speech-to-text and text-to-speech with selectable male/female voice • Caller questions matched against your built-in knowledge base using an embedded NLP/ML model bundled in-app • Local SQLite storage so everything runs without any external service I work daily with Flutter, React Native, Python and ML, and can keep the whole pipeline self-contained on the device. One question: which platforms are in scope (Android only, or Android + iOS), since fully answering live carrier calls on-device differs a lot between them? Thanks, Souvik

@Geetam00

With my extensive background and solid portfolio within full-stack development, specifically in ML and mobile app development for both iOS and Android platforms, I am well-prepared to deliver on every aspect of your Native AI Customer Support app. My expertise includes deep knowledge of Kotlin/Java for Android and Swift/Objective-C for iOS, providing you with clean native codebases that can meet even the most specific requirements. In terms of the unique components outlined in your project description, I offer strong proficiencies in on-device ML which include TTS/STT engines that can operate without external APIs. My fluency in multiple languages is also advantageous for your multilingual interaction needs and our local data storage capabilities using SQLite or similar databases ensure secure storage of your knowledge base and chat history. Not only do I have the technical know-how to build the functionalities you are seeking, but I also prioritize efficient communication and a quick turnaround time - skills that are particularly important given the complex nature of this project. My dedicated project managers, fluent in English, ensure clear lines of communication and timely response with a quick turnaround rate. Let's collaborate to create a state-of-the-art solution that exceeds all expectations!

@Huzaifa20002

I can help create a fully functional mobile app that answers calls using an on-device AI knowledge base. AIwriting assistant The app will allow users to log in via OTP, add multiple numbers, and set up a searchable database for customer inquiries. We’ll ensure that communication occurs seamlessly, including dual-voice TTS for a more engaging experience. Furthermore, the architecture will support multilingual capabilities from the start. With 5+ years of experience in mobile app development, particularly in Kotlin and Swift, I am confident in delivering a clean, robust solution that meets all your criteria. Let me know if you want to discuss further!

@ZohaibSathio

You need a fully on-device voice assistant in a native app that answers incoming calls, speaks in a male or female voice, and resolves questions from your own knowledge base — no cloud, no third-party APIs. I build exactly this. I shipped a production voice-banking platform (Urdu/English) doing 500K+ commands/month at sub-800ms, and a real-time conversational engine with a swappable, self-hosted LLM (Ollama) — no SDK lock-in, runs entirely on-device/on your own infra. Approach: on-device STT -> local LLM over your indexed product KB (RAG) -> dual-voice TTS; OTP login, up to 4 escalation numbers dialed in sequence until answered, and per-user private transcripts. Multilingual EN/Hindi (my bank IVR runs 6 languages). Native Flutter shell. Portfolio: https://www.freelancer.com/u/ZohaibSathio One question: which Android/iOS targets must run the offline model? That sets the on-device model size. — Zohaib, AI Engineer (Voice AI · Autonomous Agents · RAG)

@DanyBro

Hello, I have read your requirement and understand that you are looking for a completely native, offline AI powered call assistant that can answer business calls, respond using an on device knowledge base, and intelligently escalate calls when required without relying on any external APIs for AI, speech, or language processing. Please feel free to open a chat so we can discuss the preferred on device AI models, speech engines, and telephony implementation strategy before development begins. Muhammad Daniyal A.

@Ingjuanguzmane

Hello! I can help you with Native AI Customer Support App. My budget is 1500.0 USD for 5 days. I will review the requirements, define the implementation steps, and deliver a working result with clear progress updates. Let's discuss the details.

@hlomlan

I recently completed a project similar to yours, helping a client achieve seamless customer interactions through a custom AI solution. Your need for a native AI customer support app aligns perfectly with my expertise. I'm impressed by your detailed requirements, especially focusing on offline AI inference and multilingual support. For your project, I plan to develop a clean, professional, and user-friendly mobile app using Kotlin/Java for Android. I will prioritize smooth voice switching between male and female TTS, robust telephony integration, and secure local data storage. I offer a free consultation to discuss your project in detail, answer any questions, and tailor a solution to meet your specific needs. Let's collaborate to create a cutting-edge customer support app that exceeds your expectations. I look forward to discussing your project further.

@mrfirdosansari

Having worked in the field of web development for over 8 years, I'm well-versed with a range of technologies, including your requirement of React Native. My proficiency using this framework, coupled with my past experience on other projects that involved TTS/STT engines and native APIs, makes me an ideal candidate for your task. I understand that your project demands a completely offline AI inference system. Fortunately, I am familiar with the nuances of on-device ML - an expertise that will be vital to developing a system independent of third-party APIs or cloud services. I promise to deliver clean, native codebases with precise implementation