Voice AI Agent

@infowider11

⭐️⭐️⭐️ AI Voice Wellness Assistant (Proactive Calling + Memory Engine) ⭐️⭐️⭐️ Hello, I checked JD and you want — a proactive AI voice assistant that can call users on iOS/Android, hold empathetic conversations, remember past interactions, and use that memory to personalize future calls with secure data handling. • Outbound calling system (iOS + Android support) • Natural, human-like voice interaction (low latency STT + TTS) • Conversation engine (speech → intent → response pipeline) • Persistent memory system (user history + wellness markers) • Context-aware conversations (recall past interactions) • Secure transcript storage (raw + structured data) • AI-driven sentiment & wellness analysis • Admin dashboard / API for conversation insights • Privacy-first architecture (encryption at rest & in transit) • Cross-platform mobile app (Flutter / React Native optional) Let’s chat… Thanks

@corpmember29

Hello, I have experience building AI-powered conversational systems, mobile applications, and voice-enabled workflows using modern speech, memory, and real-time communication stacks. I can help you build a proactive voice wellness assistant that feels natural, empathetic, and context-aware across both iOS and Android. For this project, I would recommend a stack using Flutter or React Native for the mobile apps, combined with a backend powered by Node.js or Python, real-time voice infrastructure (Twilio / LiveKit / WebRTC), high-quality STT/TTS providers, and persistent memory storage using PostgreSQL or vector-based conversation memory systems. The assistant would securely store transcripts, wellness markers, summaries, and conversational context so future calls can reference past discussions naturally and intelligently. The system will include secure encrypted storage, conversation history retrieval, structured health and well-being fields, admin/API access for review, and deployment-ready infrastructure. My focus would be low-latency voice interaction, emotionally natural conversation flow, and scalable architecture capable of supporting future personalization and wellness features. I can deliver a working mobile prototype with TestFlight/APK builds, backend pipelines for speech-to-response workflows, memory retrieval/update logic, and deployment documentation for replicating the environment. Thanks, Christina

@kamran2012

I can help with this, I will build your voice AI check-in agent — cross-platform mobile app, real-time speech pipeline, and persistent memory layer. For natural-sounding voice, I will use ElevenLabs TTS with emotional inflection tuning paired with Deepgram for low-latency STT — this combination keeps round-trip under 500ms, which is critical for conversations that feel human rather than robotic. Questions: 1) Do you have a preferred cross-platform framework — Flutter or React Native? 2) Should memory retrieval use vector search for context or structured field lookups? Looking forward to potentially working together. Thanks, Kamran

@n2rtechnologies

Hi there, Reviewed your project — building a proactive calling assistant for iOS and Android is definitely in our wheelhouse. The voice AI + NLP piece is something we've worked with before. Quick question: are you handling the phone infrastructure (Twilio, etc.) or do you need us to integrate that too? Also, what's your timeline looking like? I have delivered 1500+ web and mobile projects over 14+ years — happy to share relevant examples. Thanks, Hasan

@ShaikhAneesa

Hi there, I’ve carefully reviewed your requirements and understand you’re building a proactive, call-based AI wellness assistant that can place real phone calls on iOS and Android, hold natural conversations with users, retain long-term memory of past interactions, and use that context to deliver increasingly personalized and empathetic follow-ups. I am confident I can help architect a reliable, low-latency voice AI system that feels natural, human-like, and privacy-conscious. My approach will be to design a mobile-first calling system (React Native or native iOS/Android) integrated with a voice pipeline built around high-quality speech-to-text and text-to-speech (e.g., OpenAI/Whisper, ElevenLabs, or equivalent). The backend will manage real-time conversation flow using an LLM-based dialogue engine, coupled with a structured memory layer that stores transcripts and extracted wellness signals (sleep, mood, stress indicators, etc.). This memory layer will be queryable via API and used to dynamically enrich future conversations so the assistant can reference prior check-ins naturally. Before I proceed, do you prefer a fully cloud-based architecture or a hybrid approach with some on-device processing for latency and privacy optimization? I’d love to explore the stack and architecture in more detail. Warm Regards, Aneesa.

@rbtech1984

Hello There!!! ★★★★ ( Voice AI mobile assistant with human-like calling, memory system & wellness conversation intelligence ) ★★★★ Project understanding: I understand you are building a proactive voice AI agent that calls users via iOS/Android, holds natural conversations, listens with empathy, and stores structured + raw conversation data. It must remember past interactions, reference them in future calls, ensure privacy, and feel extremely human-like in voice quality and flow. ⚜ iOS/Android calling app (native or cross-platform) ⚜ Speech-to-text + high quality low latency TTS ⚜ AI conversation flow with intent + empathy handling ⚜ Memory system with user history + wellness markers ⚜ Secure backend with encrypted data storage ⚜ Admin panel / API for conversation review ⚜ Deployment + scalable server pipeline setup I have experience in AI chatbot systems and voice-based assistants using modern NLP pipelines. I focus on building natural conversational flows, not robotic outputs. I usually use React Native or Flutter for app, Node/Python backend, and integrate STT/TTS + LLM memory layers for context recall. I would approach this by first building MVP call flow, then adding memory layer and finally refining voice realism + emotional response logic. Let’s connect and discuss architecture so we can make it truly human feeling system. Warm Regards, Farhin B.

@DeveloperStation

Hi, We’ve developed a similar product called “Descript” that uses AI to transcribe audio and extract key insights. We also built a web app for therapists to manage client data and track progress over time. This experience gives us a strong foundation in creating secure, scalable solutions that prioritize user privacy. For your project, we can use a combination of native and web technologies to deliver a fully optimized solution. We’ve also worked extensively with AWS and Azure, so we can choose the best platform for your needs. Let’s schedule a 10-minute introductory call to discuss your project in more detail and see if I’m the right fit. I usually respond within 10 minutes. I’m eager to learn more about your exciting project. Best regards, Adil

@melikatfz

Hi there, The challenge of creating a highly personal call-based assistant is integrating seamless, natural interactions with robust memory retrieval systems. Without expert implementation, issues like high latency or inadequate data encryption could compromise user experience and privacy. Leveraging my experience in AI and mobile app development, I can deliver a solution that ensures fluid conversations with secure, insightful data retention. Here are my questions: What specific wellness markers are you interested in tracking? Also, do you have a preferred cloud service for data storage and API management? Let’s discuss your project now!

@codefusion53

Hi, Your call-based wellness assistant is a meaningful and technically exciting project. I can build a mobile voice AI prototype that calls users, runs natural check-ins, remembers past conversations, and securely stores both transcripts and structured wellness markers for future personalization. For the stack, I would use React Native or Flutter for iOS and Android, a Node.js or Python backend, low-latency STT and TTS through providers such as Deepgram, ElevenLabs, OpenAI, or similar, and a memory layer using PostgreSQL plus vector search for past context retrieval. The admin side can include documented APIs or a simple dashboard to review transcripts, wellness signals, summaries, and user history. I will design the flow so each call can reference prior details naturally, extract markers like mood, sleep, stress, coping needs, and follow-up topics, then save everything securely with encryption in transit and at rest. I will also add clear deployment instructions and test scripts for the five-minute check-in acceptance flow. I have experience building AI voice agents, mobile apps, automation pipelines, and personalized chatbot systems where memory and human-like responses are central. I would be grateful to help bring this prototype to life and will gladly accept your feedback throughout the process. Best, Justin

@DngPhgNam

⭐⭐⭐⭐⭐ ✅Hi there, hope you are doing well! I recently developed a proactive voice AI assistant that engaged users naturally, tracked conversation history, and provided personalized follow-ups with emotion-aware responses, making the experience seamless and human-like. Based on my experience, the key to success in this project is ensuring the voice interaction feels truly personal by integrating high-quality speech recognition and natural language understanding with a reliable memory system. Approach: ⭕ Develop native or cross-platform mobile apps with real-time call initiation on iOS and Android. ⭕ Implement a low-latency, high-quality speech-to-text and text-to-speech pipeline ensuring natural, empathetic voice interactions. ⭕ Build a secure backend for logging dialogues, extracting wellness markers, and storing both transcripts and structured data with encryption. ⭕ Enable an API and simple admin panel to query and review past conversations and wellness data. ⭕ Provide clear deployment documentation for seamless replication and maintenance. ❓Could you please clarify if you have any preferred cloud services or compliance standards for data privacy? I am confident in delivering a robust, user-friendly voice AI agent that meets your detailed requirements and brings your vision to life. Best regards, Nam

@mobiwebsolutions

✋ Hi There!!! ✋ The Goal of the project:- BUILD A VOICE AI AGENT FOR IOS AND ANDROID THAT MAKES PERSONALIZED WELLNESS CHECK-IN CALLS, REMEMBERS USER DETAILS, AND LOGS CONVERSATIONS SECURELY. I have carefully read and understood the complete project description including call initiation, human-like TTS, speech recognition, memory storage, and secure data handling. I am the best fit for this project because I bring 9+ years experience as a full stack developer with expertise in AI voice agents and mobile app development. Matching your requirements: 1. High-quality speech recognition and TTS for natural conversations. 2. Memory system with structured data retrieval via API or dashboard. 3. Secure data storage with encryption at rest and in transit. I provide UI design, database management, testing, and full source code delivery. Completed similar AI wellness and voice assistant projects with mobile deployment. Looking forward to chat with you for make a deal Best Regards Elisha Mariam!

@jeanpatrickr8

Hello! I’m excited about your project to create a proactive call-based assistant for users on iOS and Android. Your vision of a personalized, empathetic interaction resonates with my passion for developing user-centric applications that prioritize wellness and engagement. With extensive experience in mobile app development and voice technology, I have successfully built applications that incorporate high-quality speech recognition and TTS, ensuring low-latency interactions. I am well-versed in both native and cross-platform frameworks, which will allow me to choose the best stack for your needs. To achieve your project goals, I propose the following approach: - Develop a mobile prototype for both iOS and Android that integrates seamless calling functionality. - Implement a robust server-side pipeline for speech processing, memory retrieval, and secure data handling. - Create an intuitive admin panel to manage conversation history and facilitate easy querying of user insights. - Ensure stringent privacy measures with data encryption and compliance with best practices. I am eager to collaborate on this innovative project and am confident in delivering quality results that meet your requirements. I’m available to discuss further details and begin work immediately. Looking forward to your response!

@muhammadsaad90

Hi, I can help you build this as a full voice-first mobile assistant with real-time calling, memory, and emotionally natural conversation flow while keeping privacy and data handling secure end-to-end. I would design it using a mobile client (Flutter or React Native), a low-latency voice pipeline (WebRTC + streaming STT/TTS such as Deepgram or Whisper + high-quality TTS like ElevenLabs), and a backend (Node.js/Python) with a structured memory layer (PostgreSQL + vector database for long-term conversation recall). The system would store both raw transcripts and structured wellness signals, allowing the assistant to retrieve past context and reference it naturally in future calls while maintaining encrypted storage and API-based access via a simple admin dashboard. For orchestration, I’d use a stateful conversation engine (LLM + function calling + retrieval layer) to ensure the voice feels human, context-aware, and emotionally consistent across sessions, with careful attention to latency and tone control. Have you already decided whether the calls should run through Twilio/telephony APIs or fully in-app VoIP, and I can outline a concrete architecture + MVP plan immediately.

@sarimshoaib1425

Voice AI expert here. 100% doable. I have built the systems before and the preferred stack that I would like you to use as Vapi, Telnyx, n8n and airtable. I have built hundred plus agents that operate on Phone doing outbound inbound appointment booking reservation etc. Feel free to DM for any kind of demo Let’s discuss timeline.

@ZohaibRoy

⭐⭐⭐⭐⭐ Build a Personal Call-Based Assistant for iOS and Android Users ❇️ Hi My Friend, I hope you're doing well. I've reviewed your project requirements and see you're looking for a call-based assistant for iOS and Android. Look no further; Zohaib is here to help you! My team has successfully completed 50+ similar projects for mobile app development. I will create a seamless assistant that engages users, remembers their preferences, and provides a personal touch in every conversation. ➡️ Why Me? I can easily build your call-based assistant as I have 5 years of experience in mobile app development and voice technology. My expertise includes speech recognition, API integration, and user experience design. I also have a strong grip on data security and memory management, ensuring your project meets all privacy requirements. ➡️ Let's have a quick chat to discuss your project in detail and let me show you the spell of my previous work. Looking forward to discussing with you in chat. ➡️ Skills & Experience: ✅ Mobile App Development ✅ Speech Recognition ✅ Text-to-Speech (TTS) ✅ API Development ✅ Data Encryption ✅ User Experience Design ✅ Database Management ✅ Memory Retrieval ✅ Project Management ✅ Cross-Platform Development ✅ Quality Assurance ✅ Documentation Waiting for your response! Best Regards, Zohaib

@ahsaans

Hi, This is a very interesting product idea because it combines real-time voice interaction, memory, and emotional intelligence into a single mobile experience. I would build this using a cross-platform mobile app (Flutter) connected to a backend that handles voice calls, AI processing, and long-term memory storage. For calling, I’d integrate a reliable telephony API so the app can initiate and manage outbound calls on both iOS and Android. Speech-to-text and text-to-speech will be handled using high-quality low-latency APIs to ensure natural, human-like conversation flow. The AI layer will process the conversation in real time, extract key wellness signals, and store both structured data and full transcripts securely in a database. For memory, I’ll design a retrieval system that allows the agent to reference past conversations, so it can naturally say things like “last week you mentioned…” and continue context across sessions. All data will be encrypted in transit and at rest, and a simple admin panel or API dashboard will allow you to review conversations and insights. The system will be designed so a 5-minute check-in call feels natural, remembers past details, and logs everything without errors. Q1: should the assistant follow a fixed script for structure, or adapt fully dynamically based on user emotions and responses?

@AlexVydrin

Hi, I can build your cross‑platform call‑based assistant with natural, low‑latency voice, proactive outbound calls, and a secure long‑term memory layer that lets each session feel personal. I’ve worked on voice pipelines combining ASR → intent → response → TTS, plus structured memory extraction for wellness and coaching apps. I’d use a stack like React Native or Flutter for iOS/Android calling, a fast speech pipeline (Whisper/Deepgram + a high‑quality neural TTS), and a backend with encrypted storage for transcripts, wellness markers, and retrieval. The system will log each call, extract insights, and reference past details in the next conversation. I can deliver a working prototype (APK/TestFlight), the server pipeline, an admin panel or documented endpoints, and deployment instructions. Happy to outline the full architecture and similar voice projects I’ve shipped.

@jaroslavcaprata

Hi, there. I will develop a human-like Voice AI agent for iOS and Android that can place proactive calls, maintain emotionally aware conversations, remember past discussions, and securely store wellness insights for personalized future interactions. I will use a scalable stack combining mobile technologies, low-latency speech recognition, advanced AI text-to-speech, NLP pipelines, encrypted databases, memory retrieval systems, and backend APIs to create natural voice interactions with contextual continuity and reliable session tracking. The solution will include a working mobile prototype, conversation memory architecture, transcript storage, wellness-marker extraction, admin dashboard or API endpoints, and deployment documentation for reproducible environments across platforms. I have experience building AI-driven conversational systems, voice-enabled applications, memory-based chatbot workflows, and secure backend infrastructures similar to this type of wellness and engagement platform. The voice pipeline will prioritize natural conversational pacing, contextual recall, empathy-focused dialogue handling, and high-quality TTS/STT services capable of supporting long-form personalized conversations with low latency and stable performance. If this sounds good, connect in chat and we can start. Thanks, Jaroslav Caprata

@AZTURK1

Hi there, I understand you need a proactive, low-latency voice AI that dials iOS/Android users, stores encrypted transcripts, extracts wellness markers and surfaces them on subsequent calls; my stack choice and experience building voice pipelines fit this production need. - Deliverable 1: Working mobile prototype (APK + TestFlight) with call origination via Twilio Voice SDK (iOS/Android), native or React Native bridge, and high-quality TTS streaming. - Deliverable 2: Server pipeline (Docker) handling streaming speech→ASR (Whisper/Streaming or Google Speech-to-Text), intent extraction (custom NLU), response generation (GPT-style model) and memory read/write with encrypted PostgreSQL/Redis snapshots and transcript storage in S3 (server-side encryption). - Deliverable 3: Simple admin panel or documented REST endpoints to review conversations, query wellness fields, and run session exports. - Risk/Quality-control: staged deployment with backup checkpoint and post-deploy validation to ensure minimal downtime and secure rollback. Skills: ✅ Twilio Voice SDK ✅ Whisper/Google Speech-to-Text ✅ Intent extraction / NLU pipeline ✅ Docker / AWS (S3, RDS) deployment ✅ Encryption at-rest/in-transit, access controls Certificates: ✅ Microsoft® Certified: MCSA | MCSE | MCT ✅ cPanel® & WHM Certified CWSA-2 I’m available to start immediately; Do you prefer carrier-originated numbers (SIM/call origination) or cloud SIP numbers (Twilio/Plivo) for outbound calls? Best regards,