AI Outbound Cold Calling Platform

@OutsourceMan

⭐⭐⭐⭐⭐ CnELIndia and Raman Ladhani are well-equipped to help deliver this AI-powered automated cold calling system. Our approach will include: System Architecture: We will design a scalable architecture integrating voice AI, LLM orchestration, and telephony infrastructure, ensuring smooth communication flow. Role Division: CnELIndia will handle backend automation, API integrations, and system orchestration. Raman Ladhani’s team will manage AI chatbot development and telephony infrastructure (Asterisk PBX, VoIP). Delivery Timeline: A clear timeline will be created for Phase 1, ensuring milestones are met for Lead Handling, Google Sheets integration, outbound dialing, and booking automation. Scalability: We will build the system to scale, using cloud services and modular components, ensuring it can handle larger volumes as the project progresses. Reliability & Monitoring: Implementing robust monitoring tools for real-time status updates, call quality, and system performance, ensuring reliability and minimizing downtimes. This structured approach ensures successful deployment and sets the foundation for later modules.

@ZohaibRoy

⭐⭐⭐⭐⭐ Build an AI System for Automated Cold Calls and Meeting Booking ❇️ Hi My Friend, I hope you're doing well. I've reviewed your project requirements and I see you are looking for a capable team to create an AI system for automated cold calls. You don’t need to look any further; Zohaib is here to help you! My team has successfully completed 50+ similar projects in voice AI. We will ensure a smooth process by using efficient methods and providing clear timelines within your budget. ➡️ Why Me? I can easily build your AI system for automated calls as I have 5 years of experience in voice AI and backend automation. My expertise includes telephony infrastructure, API integrations, and production deployments. Additionally, I have a strong grip on LLM orchestration and dynamic script execution, ensuring a robust solution for your needs. ➡️ Let's have a quick chat to discuss your project in detail. I’d love to show you samples of my previous work related to voice AI. Looking forward to our chat! ➡️ Skills & Experience: ✅ Voice AI Development ✅ Telephony Infrastructure ✅ Backend Automation ✅ API Integrations ✅ Dynamic Script Execution ✅ Automated Dialing ✅ Google Sheets Integration ✅ Outbound AI Conversations ✅ Event Creation ✅ Calendar Management ✅ Reliability Strategies ✅ Monitoring Solutions Waiting for your response! Best Regards, Zohaib

@CANWS

Hi Softgoway Team, We’ve deployed production AI voice-calling systems and can deliver Phase 1 with a scalable, reliable architecture. ✔ Automated outbound dialing (Singlish-capable voice AI) ✔ Dynamic scripts with interruption & objection handling ✔ Google Sheets ingestion + status sync ✔ Smart calendar booking + conflict prevention ✔ Callback automation with conversation continuity **Architecture:** Telephony (Twilio/SIP) → Voice AI (STT/TTS) → LLM orchestration → Node.js backend → Calendar/Sheets APIs → Monitoring layer. **Team:** Telephony engineer, Voice/LLM engineer, Backend developer, DevOps specialist. Built for scale, monitored for reliability, ready for long-term expansion.

@usamae

Hey, I've built similar voice AI systems before - automated calling with natural conversation flow, interruption handling, and calendar integration. The Singlish requirement is interesting, shouldn't be a problem with proper prompt engineering. For this project, I'd use something like Twilio for telephony + a voice AI platform (Vapi or similar) + your LLM of choice for the conversational layer. Google Sheets integration is straightforward, and the callback/booking logic can sit in a Node backend with proper state management. I can handle the full stack here - backend automation, API integrations, voice AI setup, and deployment. I've done production deployments before so monitoring and reliability are baked in from the start. Quick question - do you have a preferred voice AI provider, or are you open to recommendations? Also, for the Singlish accent, do you want actual voice synthesis in that style or just the conversational patterns? I can have a working prototype ready in about a week, then we refine and scale from there. Let me know if you want to see any past work or discuss the approach in more detial. - Usama

@mahig47

Hello As per your project post, you are looking to build an AI Outbound Cold Calling Platform that can automatically call leads in Singlish, qualify prospects, and book meetings while managing callbacks and lead status. The goal is to create a production ready, scalable voice AI system that handles outbound conversations reliably and integrates seamlessly with calendars and lead sources. My approach will focus on developing a robust voice AI system with Google Sheets lead ingestion, automated dialing, dynamic script execution, and real time objection and interruption handling. I will implement calendar availability checks, conflict prevention, automated event creation, and invite sending, along with callback scheduling and conversation continuity tracking. The platform will include a scalable backend, monitoring, and reliability mechanisms to support production deployment and future scaling. I specialize in building voice AI platforms, conversational automation systems, and scalable backend architectures using LLMs, telephony APIs, speech synthesis, and cloud infrastructure. My focus is on delivering reliable, production ready systems with clear architecture, monitoring, and performance optimization. I am confident I can help you build a scalable, production ready AI cold calling platform with strong reliability and future expansion capability. Let us connect to discuss your deployment plan and delivery roadmap. Best regards Nikita Gupta

@arbu1499

Hi Softgoway, your Phase 1 scope—AI cold calling in Singlish with automated dialing, dynamic script execution, objection handling, and end-to-end booking with calendar conflict prevention—aligns perfectly with voice AI systems we’ve deployed in production. We’ve built telephony-integrated solutions with LLM orchestration, Google Sheets ingestion, callback automation, and real-time monitoring to ensure reliability at scale. I can share a clear system architecture, defined team roles (telephony, voice AI, backend, DevOps), and a practical timeline focused on scalability and uptime from day one. We’re confident in delivering a production-ready module that sets a strong foundation for your long-term roadmap. Looking forward for your positive response in the chatbox. Best Regards, Arbaz H

@vishal1145

Your Asterisk + LLM integration will fail in production if you don't implement proper interrupt detection - most voice AI systems I've audited break when prospects talk over the bot mid-sentence, causing awkward pauses and dropped context. That's the difference between a demo and a system that actually books meetings. Before architecting this, I need clarity on two things: What's your expected concurrent call volume during peak hours, and are you planning to use Twilio/Vonage for carrier connectivity or self-hosted SIP trunking? This determines whether we build on WebRTC or traditional RTP streams. Here's the architectural approach: - ASTERISK PBX + AGI: Deploy FreeSWITCH with custom AGI scripts for call control, implementing barge-in detection using VAD thresholds to handle Singlish speech patterns and interruptions without losing conversation state. - VOICE AI ORCHESTRATION: Integrate Deepgram for real-time STT with custom Singlish acoustic models, route transcripts to GPT-4 via streaming API, then synthesize responses using ElevenLabs with sub-800ms latency to maintain natural conversation flow. - PHP BACKEND + GOOGLE SHEETS API: Build event-driven workers that poll Sheets for leads, update call status via batch writes, and trigger Asterisk AMI commands for automated dialing with retry logic and timezone-aware scheduling. - CALENDAR INTEGRATION: Implement bidirectional Google Calendar sync with conflict detection using freebusy queries, atomic booking transactions to prevent double-bookings, and automated invite generation with Zoom links. - CALLBACK STATE MANAGEMENT: Store conversation transcripts and sentiment scores in PostgreSQL, trigger scheduled redials via cron jobs, and inject previous context into LLM prompts to maintain continuity across multiple touchpoints. I've deployed 4 production voice AI systems that handled 50K+ calls monthly, including one for a Singapore-based sales team that required Singlish NLP tuning. I don't take on telephony projects without understanding your carrier SLAs and failover requirements first. Let's schedule a 20-minute technical call to walk through edge cases like dropped connections and API rate limits before you commit budget.

@webmasters486

Hi there, We are ready to deliver the first production module of your AI-powered cold-calling system with full Singlish support, lead qualification, and automated meeting booking. Our team has prior experience deploying voice AI systems in production and can handle telephony infrastructure, LLM orchestration, backend automation, and API integrations seamlessly. For Phase 1, we will implement Google Sheets lead ingestion, dynamic script execution, interruption handling, automated dialing, calendar booking with conflict prevention, and callback automation ensuring conversation continuity. We’ll provide a clear system architecture, define team roles, outline a delivery timeline, and detail scalability, reliability, and monitoring strategies to ensure a robust deployment. Our approach prioritizes maintainable, production-ready code with clear documentation, allowing smooth transition into subsequent modules and long-term expansion. Best regards, Muhammad Adil Portfolio: https://www.freelancer.com/u/webmasters486

@Solutionzhere

This is not a “demo bot” build, it’s full telephony + voice AI orchestration. We’ve deployed production outbound voice systems using programmable telephony with LLM-driven dialogue control. Being direct: $250–750 is not realistic for automated dialing, Singlish voice tuning, booking logic, retries, monitoring, and production hardening. Realistic Phase 1 estimate: $6,000 – 9,000 USD Timeline: 5–7 weeks High-Level Architecture: Telephony layer via Twilio (or equivalent SIP provider) Real-time voice AI + interruption handling (LLM orchestration layer) Backend (Node/Python) for lead ingestion + state tracking Google Sheets sync + booking via Google Calendar API Callback scheduler + conversation memory store Monitoring, logging, fallback & retry logic Team Roles: Telephony engineer, AI orchestration engineer, backend/API engineer, DevOps. Built scalable (queue-based workers + stateless call handling). One key question: Do you already have a Singapore-registered outbound calling number and compliance clearance for automated calls?

@kishanbwts

I’ve worked on voice AI projects that manage complex call flows and objection handling in production environments, which helps me understand the challenges here. For your system, I’d start by designing a clear architecture that tightly integrates Google Sheets ingestion with the outbound dialing and dynamic script control to maintain conversation context even during interruptions. To handle Singlish naturally, we can fine-tune language models and test against regional phrases to improve objection responses. For booking, syncing calendar availability with conflict prevention via API hooks will ensure smooth scheduling and reduce errors. How do you plan to handle data privacy and call consent during lead ingestion? Also, would you prefer using an open-source telephony stack or a cloud service to support scalability? We’ll set up monitoring dashboards to track call success, AI response accuracy, and system uptime. I can quickly produce a detailed timeline breaking down phased delivery and team roles covering telephony, voice AI, and backend automation. Ready to start mapping out the system architecture and delivery plan now.

@sarbtech123

As an AI and automation specialist with a strong emphasis on Python development, I am eager to bring my extensive experience-building backend systems and automation to your project of building an AI Outbound Cold Calling Platform. My five-plus years dedicated to Python has helped me hone skills not only in scripting but also in managing, monitoring, and scaling. A key strength of mine is ensuring production-readiness, which aligns perfectly with your project's demand for clear system architecture and support for role division within the team. Moreover, my expertise in API integrations gives me an upper hand in creating dynamic and smooth modules such as Google Sheets ingestion, automated dialing, dynamic script execution, and interruption & objection handling. Choosing me means choosing a business-focused engineer who designs solutions while maintaining a production-ready mindset. I assure you of regular communication, realistic timelines, and transparent delivery because I respect the value of time and money. I'm excited about the long-term vision you mentioned, where successful teams will be invited to later modules and larger budgets. Let's not only meet expectations but exceed them together.

@AlexDeveloper911

Hi, We would like to grab this opportunity and will work till you get 100% satisfied with our work. We are an expert team which have many years of experience on PHP, Software Architecture, Asterisk PBX, VoIP, AI (Artificial Intelligence) HW/SW, API Integration, AI Chatbot Development, AI Development Lets connect in chat so that We discuss further. Thank You

@KarthikTechCon

Hi Softgoway, I’m Karthik, AI Systems Architect with 15+ years of experience building production-grade AI + automation platforms, including real-time LLM orchestration and cloud telephony integrations. Your Phase 1 scope requires tight coordination between telephony, voice AI, LLM orchestration, and calendar automation — not just a chatbot. Proposed Architecture ✔ Telephony Layer – Twilio / Vonage programmable voice – SIP trunk support – Automated outbound dialing logic ✔ Voice AI Stack – Real-time STT (Deepgram / Google STT) – TTS with Singlish-adapted voice model – Low-latency streaming pipeline ✔ LLM Orchestration – Structured prompt flows – Objection handling logic tree – Conversation state persistence – Callback scheduling & continuity ✔ Booking Engine – Google Calendar API integration – Availability checks + conflict prevention – Automated invite dispatch ✔ Lead Handling – Google Sheets ingestion – Status updates + CRM sync Reliability & Scale – Async job queues – Call monitoring & retry logic – Metrics dashboard (success rate, drop rate, booking rate) – Cloud-native deployment (AWS/GCP) I can provide: • Clear architecture diagram • Team role breakdown • 6–8 week delivery plan • Monitoring & scaling strategy If you’re serious about a production-ready AI cold-calling engine, I’d be glad to discuss Phase 1 in detail.

@SkillCrafts

I’ve successfully deployed low-latency conversational AI agents for high-stakes sales, focusing on the critical sub-500ms response window that prevents "robotic" pauses. My experience building automated outbound systems involves integrating high-fidelity voice synthesis with real-time intent recognition, ensuring every lead interaction feels fluid rather than scripted. Having built similar AI telepresence modules, I understand the technical nuances of managing concurrent call streams while maintaining high audio quality and data integrity across thousands of dials. To deliver this module, I will implement a WebSocket-driven architecture using Vapi or Retell AI, combined with Deepgram’s Nova-2 for near-instant speech-to-text. The core logic will rely on GPT-4o-mini for rapid decision-making, utilizing Function Calling to synchronize call outcomes directly with your CRM via custom FastAPI webhooks. I’ll leverage Twilio’s Programmable Voice for robust outbound SIP trunking, ensuring we scale call volume while maintaining adherence to STIR/SHAKEN protocols. Each call will conclude with an automated summary and sentiment analysis layer to provide your team with actionable, structured data from every outbound attempt. Are we focusing on a specific caller "persona" to ensure the LLM’s tone is perfectly dialed in for your target demographic? Does the system need to support human-in-the-loop handoffs, or is the priority strictly on autonomous lead qualification? I’m available for a brief call to discuss your latency requirements and can begin architectural mapping as soon as we align on the API stack.

@mayankinnovative

Automated cold calling at production scale fails when voice, orchestration, and telephony are stitched together without clear state control. You’re not just building a bot; you’re deploying a real-time decision system that must handle latency, objections, booking logic, and redial continuity reliably. Our approach for Phase 1: Architecture: Telephony layer (SIP/Twilio equivalent) → Voice AI (ASR + TTS tuned for Singlish phonetics) → LLM orchestration layer with structured dialogue state → Backend (Node/Python) managing Sheets ingestion, status updates, booking APIs, and callback scheduler → Central database for conversation memory and audit logs. Lead flow: ingest from Google Sheets, normalize, enqueue, and update status via webhook callbacks. Conversation engine: dynamic script tree with interruption handling, objection classification, and fallback guardrails to avoid hallucinated commitments. Booking: real-time calendar check, atomic slot locking, event creation, and invite dispatch. Callback automation: scheduled redials with persisted context for continuity. Team roles: • Telephony/VoIP engineer • Voice AI + speech optimization specialist • LLM orchestration/backend engineer • DevOps for deployment, monitoring, autoscaling Timeline: 6–8 weeks to stable production pilot. Scalability: stateless workers + queue-based dialing. Reliability: call logging, latency monitoring, failover routing, structured analytics.

@bhartimalu

Hello, I can help you build and/or run your outbound cold calling platform with reliable call workflows, CRM integration, and reporting — so you can reach prospects, log interactions, track performance, and generate real business conversations. I’ll set up efficient dialling and call scripts, handle caller training or automation logic, and ensure clean logs and analytics for optimisation. Whether you need a system built or someone to drive results using cold calling tools and lists, I deliver professional, results-focused work. Ready to start and deliver a stable outbound calling solution that improves connection and conversion. Regards, Bharti

@nicolasalexandro

Hey — saw your post about building an AI outbound cold calling platform. Biggest risk on v1 is the gap between “it technically works” and “it actually sounds human enough to not get hung up on in 3 seconds.” Quick question before I suggest an approach: Do you already have a preferred LLM/voice stack (e.g. OpenAI + ElevenLabs), or are you open to recommendations based on latency and cost per call? I’ve worked on AI calling / conversational AI flows before, especially around detection of intent, call routing, and making the agent sound natural under real-world conditions. If you can send over your current spec, call flow diagrams, or any sample scripts, I’ll review them and outline what’s realistic for your first production module.

@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

@devpratiksha

Hello There! I carefully read the full job description for AI Outbound Cold Calling Platform and understand that you are looking for a production-ready system that automates outbound calls, handles Singlish conversations, qualifies leads, and schedules meetings. Phase 1 focuses on ingesting leads, dynamic AI-driven calls, callback automation, and reliable booking with calendar integration. AI Outbound Cold Calling Platform will process lead data from Google Sheets, execute dynamic scripts via voice AI, handle interruptions and objections, track call statuses, and create calendar events while maintaining continuity for callbacks. The backend will ensure scalable telephony orchestration, LLM-driven conversation logic, and monitoring for reliability. Core features likely include automated dialing, AI conversation handling, lead status management, callback scheduling, calendar integration. I have 7+ years of experience in backend automation, telephony infrastructure, AI orchestration, and production deployment, I design robust, scalable systems with monitoring, logging, and modular architecture for long-term maintenance and iterative enhancements. Let us schedule a quick chat to align your vision and next steps. Warm Regards, Pratiksha Gupta