Open-Source phone Assistant Stack

@n2rtechnologies

Hi there, I reviewed your requirements and this looks like something we can handle well. Building a production-ready voice assistant stack for restaurants is complex—the NLP + Twilio integration piece especially needs solid architecture to scale reliably. I have a couple of questions about your MVP scope and whether you're leaning toward existing models or custom training. Happy to hop on a quick call to discuss. I have delivered 1500+ web and mobile projects over 14+ years — happy to share relevant examples. Thanks, Hasan

@OutsourceMan

With my team's skills in AI development and Mobile App Development, we can provide you with a state-of-the-art open-source phone assistant stack that meets all your specifications and more. Over the past 18 years, my team and I at CnELIndia have honed our ability to create efficient, high-performing apps that address business needs with precision. Our past projects cover a wide range of industries, giving us the adaptability necessary to create a tailored solution for your restaurant industry challenges. Specifically, our expertise in React Native positions us uniquely to deliver a seamlessly integrated system that operates equally well on Android and iOS platforms. And as you highlighted the need, we excel in containerised codebase which affords stress-free local installation without proprietary dependencies. In line with your expectations, here’s what you can confidently anticipate from us: effective architecture diagrams, custom language and intent models for restaurants scenarios, a deployable codebase with setup scripts, comprehensive documentation for maintenance/feature expansion, and dashboards capable of presenting vital statistics/transcripts etc. Additionally, our years-long experience with working to sub-second response times on contemporary mobile hardware makes us confident that your acceptance criteria will be comfortably met.

@AITSoft

Hello, I understand you want an open-source voice assistant for restaurants that can handle orders, answer questions, and give recommendations smoothly during calls. I would start by designing a clear system with easy-to-use, containerized code you can deploy locally without licenses. I will create custom language models to suit restaurant needs and build a demo app for Android/iOS to show the full experience. Plus, I'll develop a dashboard for call stats and transcripts. My goal is to meet your benchmarks like fast response times and high accuracy even with background noise, ensuring easy setup and ongoing maintenance. To clarify your needs better, could you share which restaurant ordering systems or POS integrations you currently use? Are there specific menus or types of modifiers to focus on initially? Do you prefer voice recognition to be done fully offline, or is some cloud processing acceptable? What languages or accents should the assistant support? Finally, how soon do you want the minimum viable product to be ready? Which existing restaurant systems or POS would you like the assistant to integrate with first? Thanks,

@Herculesz

Hi I can build a production-ready open-source voice AI stack for restaurants that handles live phone calls, order taking, FAQs, and personalized recommendations with a clean path to broader retail use later. The main technical challenge is achieving commercial-level call performance while keeping latency low, speech recognition stable in noisy environments, and order logic accurate for modifiers, special instructions, and follow-up questions. My solution is a fully containerized architecture using streaming ASR, intent/entity extraction, dialogue orchestration, retrieval-backed knowledge responses, call transcript storage, and a stats dashboard for call outcomes, transcripts, and performance metrics. I work with Node.js/Python backends, telephony integration, real-time audio pipelines, speech-to-text, NLP/NLU tuning, recommendation logic, Docker deployment, and analytics dashboards. For restaurant scenarios, I can structure custom intent and slot models around menu items, combos, substitutions, allergens, store policies, hours, and location-specific handling. The deliverable can include deployable code, setup scripts, architecture documentation, training/maintenance guides, and a demo tablet app that shows ordering, Q&A, and recommendation flows end to end. Most importantly, I would design the stack without proprietary lock-in so it remains installable locally, extensible, and practical for ongoing training and expansion. Thanks, Hercules

@ShaikhAneesa

Hi there, I’ve carefully reviewed your project and understand you need a fully open-source, production-ready voice AI system that can handle restaurant calls end-to-end with accurate ordering, real-time responses, and scalable architecture comparable to commercial solutions. My approach begins with designing a low-latency architecture using open-source speech-to-text, LLM-based intent handling, and text-to-speech, orchestrated through a telephony layer such as Twilio or SIP. I will ensure sub-second response flow by optimizing streaming pipelines and lightweight model routing. Next, I will build custom intent and entity models tailored for restaurant use cases, covering orders, modifiers, FAQs, and recommendations. The system will maintain conversational context so it can handle complex, multi-step orders and personalized suggestions. I will then deliver a containerized stack with setup scripts for easy local deployment, along with a demo mobile app showcasing ordering, Q&A, and recommendation flows. A dashboard will also be included to track call logs, transcripts, and key performance metrics. Finally, I will provide clear documentation covering setup, training, scaling, and future enhancements so the system remains fully extensible without proprietary dependencies. What’s your priority for the MVP; maximizing voice accuracy in noisy environments or optimizing latency for faster conversations? Let’s build something powerful and scalable. Warm regards, Aneesa.

@ixorawebmob

Hello, I’ve gone through your project details and this is something I can definitely help you with. With over 10 years of experience in mobile and web app development, including AI and voice assistant technologies, I’m confident in delivering a production-ready open-source stack tailored for your restaurant application. I focus on clean architecture and scalable code, ensuring that your voice AI assistant performs flawlessly, especially in noisy environments. I will create a robust architecture diagram and tech stack rationale, along with a containerized codebase for easy deployment. Additionally, I’ll develop custom language models specific to restaurant scenarios and provide a demo app for both Android and iOS. Clear documentation will also be included for ongoing maintenance and training. Here is my portfolio: https://www.freelancer.in/u/ixorawebmob I’m interested in your project and would love to understand more details to ensure the best approach. Could you clarify: Do you have a specific timeline in mind for the project’s completion? Do you have a specific timeline in mind for the project’s completion? Let’s discuss over chat! Regards, Arpit Jaiswal

@temoberishvili

Hello, This is a solid and ambitious project—I understand you’re aiming for a fully open-source, production-ready voice AI system that can handle real restaurant calls with high accuracy and low latency. I’ve built AI-driven systems combining speech-to-text, LLM orchestration, and real-time telephony, and can design an end-to-end stack that’s modular, scalable, and fully containerized. The focus will be on fast inference, reliable intent handling, and clean extensibility for future retail use cases. I can deliver a complete architecture (ASR + NLU + dialog manager + TTS + telephony layer), optimized models for restaurant workflows, and a working demo app with dashboard + analytics. Everything will be deployable locally via Docker with no proprietary lock-in. Performance targets like sub-second responses and high intent accuracy can be achieved using optimized pipelines and fine-tuned models with noise-robust datasets. Happy to share similar AI/voice system work and outline milestones clearly.

@rbtech1984

Hello There!!! ★★★★ ( Build an open-source voice AI assistant stack for restaurants ) ★★★★ I understand you need a production-ready open-source voice AI assistant that handles orders, answers customer queries, and gives personalized recommendations with high accuracy, deployable on Android/iOS, containerized, and easily maintainable. ⚜ Design architecture and choose optimal tech stack ⚜ Containerize and provide setup scripts for easy deployment ⚜ Develop custom language and intent models for restaurants ⚜ Build demo app showcasing key user flows ⚜ Create dashboard for call transcripts and analytics ⚜ Ensure sub-second response time and ≥95% intent accuracy ⚜ Provide clear documentation for training and maintenance I’ve built AI voice assistants and mobile integrations before, focusing on NLP accuracy and smooth deployment. I’ll deliver a robust, extendable system tuned for noisy restaurant environments. Warm Regards, Farhin B.

@melikatfz

Hello there, I'm thrilled about the opportunity to collaborate on developing an advanced voice AI assistant tailored for restaurants and retail businesses. With a focus on delivering performance comparable to commercial solutions, I understand the importance of creating a seamless end-to-end system that accurately handles order-taking, responds to customer inquiries, and provides personalized recommendations. My team and I have extensive experience in AI development, particularly in natural language processing and machine learning, ensuring the assistant can smoothly handle phone calls with sub-second response times and high intent recognition accuracy. Could you share more about your preferred technology stack or any existing tools you would like to integrate with this system? Additionally, how do you envision the role of the dashboard in day-to-day operations, and what key metrics are you most interested in tracking? I would love to discuss your project further and explore how we can bring your vision to life. Looking forward to connecting soon!

@chandankandar007

As a full-stack developer with over 13 years of experience, I bring deep and diverse skills to the table. Firstly, in terms of mobile app development, I'm highly proficient in both React Native and Flutter, which permits me to seamlessly build cross-platform apps for Android and iOS. Morever , my knowledge of AI-API integrations will be particularly valuable to this project, having worked with tools like MetaAI, OpenAI and Google AI APIs. Distinctly, these skillsets have positioned me favorably towards system building and data handling - all critical aspects for your voice AI assistant. Drawing from my years working on backend systems including REST API and real-time sockets, I am both familiar and comfortable architecting scalable module designs for tasks similar to the defined scopes of your project. My strength in secure application design is pivotal to ensuring that all interactions between your assistant and its users are securely encrypted- such as voice/video streaming and customer data encryption. Lastly, my adherence to strategic planning aligns well with what you seek i.e structured documentation that will serve as a pragmatic guide for ongoing training, maintenance, and feature expansion post handover. In summation, partnering your team on this not only means a bespoke value-driven solution but a commitment to respect agreements and always deliver the best possible outcome. Let's make this happen! Thank you for considering my profile.

@GameOfWords

As a team that can expertly blend cutting-edge technology like Artificial Intelligence and Mobile App Development, we are excited to tackle your project's needs. We understand the criticality of having a voice AI assistant in today's business climate, which is why we have dedicated time and resources into honing our skills in this arena. Our portfolio showcases our ability to optimize WordPress sites, extending their functionality, incorporating advanced features, and even integrating AI-driven automation - all skill sets that match your requirements. We pride ourselves on tailoring solutions to meet specific business goals efficiently, and this aligns perfectly with your quest for a production-ready open-source stack. Not only will we create a comprehensive architecture diagram and tech stack rationale but as requested, we will provide containerized codebases equipped with setup scripts - all designed for hassle-free local installation. Through clear documentation and regular training tips not only will you have a powerful end-product but you'll also be armed with the necessary tools to maintain and expand its feature set flawlessly. Let's actualize your vision!

@DngPhgNam

⭐⭐⭐⭐⭐ ✅Hi there, hope you are doing well! I have developed a similar open-source voice assistant system for retail, which processed voice orders and customer queries seamlessly through a custom ML model and mobile app integration. The most critical part for success here is ensuring a finely tuned NLP model that adapts precisely to noisy restaurant environments for accurate intent recognition. Approach: ⭕ I will design a scalable architecture diagram with clear tech stack choices ⭕ Develop containerized deployment with automation scripts ⭕ Build custom language and intent models optimized for restaurant scenarios ⭕ Create a demo mobile app showcasing order taking, FAQs, and personalized recommendations ⭕ Assemble comprehensive documentation and a powerful dashboard for call analytics ⭕ Optimize performance for sub-second response on mobile hardware with high accuracy ❓ Could you please clarify if you have preferred cloud hosting or on-premise requirements? I am confident in delivering a robust, user-friendly, and fully open-source voice AI assistant that meets your performance and deployment expectations. Looking forward to collaborating with you. Best regards, Nam

@mughiraaa

Hello, I will design the architecture using python with fastapi for the backend to handle requests, dialog management, and database interactions, and node.js for real-time audio streaming. the voice assistant will use custom-trained nlu models for intent recognition, slot filling, and entity extraction, with postgresql storing menu items, orders, and customer history. audio input and output will be processed using speech-to-text and text-to-speech models optimized for noisy environments, and the mobile demo will run on an android tablet using react native to handle calls, display the menu, and show recommendations. docker containers will hold all components for easy deployment, and a dashboard built in vue.js will track conversations, orders, and statistics. Let's have a detailed discussion, as it will help me give you a complete plan, including a timeline and estimated budget. I will share my portfolio in chat I look forward to hear from you. Thanks Best Regards, Mughira

@justinw45

Hello, I understand you are in need of a comprehensive open-source stack for running a voice AI assistant tailored for restaurants and retail businesses. The core capabilities include accurately taking orders, answering customer inquiries, and providing personalized recommendations. The assistant must operate smoothly during phone calls, ensuring a seamless customer experience. To address your requirements, I propose developing a robust architecture with a rationale for the tech stack, a deployable codebase with setup scripts, custom language and intent models, a demo app for showcasing user flows, detailed documentation for training and maintenance, and a dashboard for monitoring statistics and call transcripts. I am well-equipped to deliver a solution that meets your criteria for sub-second response time, high intent recognition accuracy, and hassle-free installation. I am eager to discuss further details regarding the timeline and milestones to ensure successful project completion. Best regards, Justin

@hassans5

Hello! I understand you’re aiming to build a production-ready, open-source voice AI assistant that can handle restaurant orders, customer queries, and personalized recommendations with high accuracy and low latency. I have experience designing end-to-end AI systems with speech-to-text, intent recognition, and real-time response pipelines, and I can deliver a containerized, scalable stack with a clear architecture, custom-trained models, and a live demo app. I’ll ensure sub-second responses, strong intent accuracy in noisy environments, and a full dashboard with call transcripts and analytics. I’m confident I can provide a clean, extensible system ready for real-world deployment. Looking forward for your positive response in the chatbox. Best Regards, Hassan T

@Techroj

Dear Client, Greetings!! I have carefully reviewed your project requirements and am confident that I can deliver a complete, production-ready open-source voice AI assistant tailored for restaurant and retail use cases. With 7+ years of hands-on experience in Python, AI/ML, NLP, and end to end software development, I have built scalable systems involving speech recognition, intent modeling, and real-time conversational pipelines. I can provide a well structured architecture with containerized deployment , custom trained intent and language models optimized for noisy environments, and seamless phone integration using platforms like Twilio. The solution will include a responsive mobile demo app, a dashboard for analytics and call transcripts, and clear documentation for future training and scaling. My focus will be on achieving sub-second response times and high intent accuracy through optimized models and efficient system design all without proprietary dependencies. I have also worked with global clients and platforms like Upwork, Fiverr, and Freelancer, ensuring reliable delivery and communication. I’d be happy to discuss milestones and timelines to move forward. Regards, Rojan.U

@sekai1116

⚡As a seasoned Full-Stack & Mobile App professional⚡ in the AI domain, I possess a broad array of skills that make me an ideal candidate for your Open-Source phone Assistant Stack project. In the past eight years, I have honed my expertise in AI Chatbot Development, Natural Language Processing, and Voice Assistance Devices to create high-performance applications for web and mobile platforms. Leveraging my proficiency in backend (Node.js, Python/Django), frontend (React Native), and cloud computing (AWS, Azure, GCP), I am well-prepared to design and develop a cutting-edge voice AI assistant stack specifically tailored to the needs of restaurants and retail businesses. Having worked across various industries like FinTech, Healthcare, E-commerce, Travel, and EdTech, I appreciate the unique demands of different sectors. This experience enables me to design resilient solutions that not only guarantee sub-second response times but also exhibit exceptional intent recognition accuracy in noise profiles typical of restaurants. Additionally, my commitment to generating comprehensive documentation and providing ongoing training support ensures hassle-free maintenance and feature expansion—prerequisites you've identified as key aspects of this project. Join hands with me to achieve your goal of a production-ready open-source system potent enough to compete with commercial offerings in performance. Let's rock this project together!

@haseebsidd07

Hey , I just finished reading the job description and I see you are looking for someone experienced in Twilio, iPhone, Voice Assistance Devices, AI Chatbot Development, Android, AI Development, Machine Learning (ML), Mobile App Development, Deep Learning and Natural Language Processing. This is something I can do. Please review my profile to confirm that I have great experience working with these tech stacks. While I have few questions: 1. These are all the requirements? If not, Please share more detailed requirements. 2. Do you currently have anything done for the job or it has to be done from scratch? 3. What is the timeline to get this done? Why Choose Me? 1. I have done more than 250 major projects. 2. I have not received a single bad feedback since the last 5-6 years. 3. You will find 5 star feedback on the last 100+ major projects which shows my clients are happy with my work. Timings: 9am - 9pm Eastern Time (I work as a full time freelancer) I will share with you my recent work in the private chat due to privacy concerns! Please start the chat to discuss it further. Regards, Haseeb,

@SkillCrafts

Building a high-concurrency, low-latency AI voice stack for hospitality requires moving beyond generic wrappers to a robust, self-hosted infrastructure. I recently deployed a similar real-time voice pipeline, migrating a client from high-cost proprietary APIs to a custom stack that reduced end-to-end latency to sub-500ms while maintaining natural, human-like conversational flow. My priority is delivering a production-ready system that handles simultaneous restaurant bookings and complex retail inquiries without the "robotic" lag typical of poorly optimized telephony integrations. I will implement the LiveKit Agents framework as the core orchestration layer, leveraging Deepgram’s Nova-2 for ultra-fast STT and Cartesia or high-performance open-source alternatives like Piper for expressive TTS. For the logic engine, I’ll deploy a fine-tuned Llama 3 model via Groq or a self-hosted vLLM instance to handle intent extraction and multi-turn booking workflows. The architecture will include a FastAPI middleware to interface directly with restaurant POS systems or internal databases, containerized via Docker for seamless multi-tenant deployment across diverse retail environments. Are you planning to support specific reservation APIs like OpenTable or Resy, or should we build a custom calendar sync for these businesses? Also, do you have a preference for the SIP provider, or would you like me to recommend a low-latency solution like Telnyx for the telephony handoff? I am open to a brief technical sync to discuss latency benchmarks and how we can optimize the conversational UX for noisy restaurant environments.