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Automation JavaScript MySQL PHP Software Architecture
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Juan

@juanpablomacf

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4.8
22

6.5

6.5

96%

AI/ML/RAG & Automation | AI Voice, Web, n8n, GHL

$50 USD / Hour

・

Flag of CHILE

Chile (9:04 AM)

・

Joined on January 28, 2026

・

2 Recommendations

I transform complex business challenges into scalable AI solutions that deliver measurable results. With over a decade of experience in both full-stack development and AI implementation, I bridge the gap between ambitious ideas and production-ready systems. 🏆 Proven Impact Across Industries FinTech: Built trading dashboards processing 50,000+ daily transactions with real-time analytics MedTech: Developed AI diagnostic assistants that reduced analysis time by 65% LegalTech: Implemented RAG systems that cut legal research from hours to minutes SaaS: Scaled platforms from MVP to 100,000+ users with integrated AI capabilities 🔧 Technical Expertise AI & Machine Learning AI Agent Systems: Multi-step reasoning and workflow orchestration RAG Pipelines: LangChain, LlamaIndex, Pinecone, ChromaDB (95%+ retrieval accuracy) LLM Integrations: GPT-4, Claude 3, LLaMA fine-tuning and optimization Voice AI: Twilio integration and real-time call processing Full-Stack Development Frontend: React/Next.js, TypeScript Backend: Node.js, Python, FastAPI DevOps: AWS, Docker, Kubernetes, CI/CD pipelines Automation: n8n workflows, custom API integrations 🚀 Recent Deliverables • AI Customer Support: Reduced ticket volume by 75% with bots handling 15,000+ monthly conversations • Document Intelligence: Built legal document analysis that cut review time from 4 hours to 15 minutes • Trading Analytics: Delivered real-time dashboards with 99.9% uptime for financial clients • Workflow Automation: Saved 200+ manual hours monthly through n8n-powered processes 🎯 My Approach Strategy & Planning Technical feasibility analysis and ROI-focused project scoping Scalable architecture design for long-term growth Execution & Delivery AI-enhanced development using Cursor and Copilot Agile methodology with transparent weekly progress updates Comprehensive testing and quality assurance Production Excellence Robust monitoring, logging, and error handling Performance optimization and thorough documentation 📈 Why Choose Senior Expertise? I architect systems that scale, implementing proper error handling, security protocols, and maintainable codebases. My clients avoid technical debt while accelerating their AI roadmap with production-ready solutions. I'm available for full-time engagements and ready to discuss how I can help bring your AI vision to life.

Verifications

On time

95%

On budget

94%

Accept rate

82%

Repeat hire rate

12%

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Portfolio

Portfolio

13793671
ngineered a high-performance automotive data platform that aggregates, normalizes, and serves structured vehicle data from top-tier sources like Car and Driver. The system featured a multi-source orchestration layer (Apache Airflow) managing Python-based collectors that processed detailed review texts, performance specs (0-60 mph, MPG), expert ratings, and pricing from HTML, PDFs (road test sheets), and RSS feeds. Data was cleansed, deduplicated, and stored in a time-series optimized PostgreSQL database. The core was a low-latency GraphQL API (Apollo Server/Node.js) allowing complex queries (e.g., "find all SUVs with >300 hp and a Car and Driver rating >8/10"). The consumer-facing frontend (Next.js 14, App Router) was a dynamic comparison tool with side-by-side spec sheets, interactive data visualizations of performance metrics, and personalized "vehicle matching" based on user-selected priorities. The entire system was built for scale using event-driven archi

Automotive Media API & Vehicle Comp

ngineered a high-performance automotive data platform that aggregates, normalizes, and serves structured vehicle data from top-tier sources like Car and Driver. The system featured a multi-source orchestration layer (Apache Airflow) managing Python-based collectors that processed detailed review texts, performance specs (0-60 mph, MPG), expert ratings, and pricing from HTML, PDFs (road test sheets), and RSS feeds. Data was cleansed, deduplicated, and stored in a time-series optimized PostgreSQL database. The core was a low-latency GraphQL API (Apollo Server/Node.js) allowing complex queries (e.g., "find all SUVs with >300 hp and a Car and Driver rating >8/10"). The consumer-facing frontend (Next.js 14, App Router) was a dynamic comparison tool with side-by-side spec sheets, interactive data visualizations of performance metrics, and personalized "vehicle matching" based on user-selected priorities. The entire system was built for scale using event-driven archi

Automotive Media API & Vehicle Comp

ngineered a high-performance automotive data platform that aggregates, normalizes, and serves structured vehicle data from top-tier sources like Car and Driver. The system featured a multi-source orchestration layer (Apache Airflow) managing Python-based collectors that processed detailed review texts, performance specs (0-60 mph, MPG), expert ratings, and pricing from HTML, PDFs (road test sheets), and RSS feeds. Data was cleansed, deduplicated, and stored in a time-series optimized PostgreSQL database. The core was a low-latency GraphQL API (Apollo Server/Node.js) allowing complex queries (e.g., "find all SUVs with >300 hp and a Car and Driver rating >8/10"). The consumer-facing frontend (Next.js 14, App Router) was a dynamic comparison tool with side-by-side spec sheets, interactive data visualizations of performance metrics, and personalized "vehicle matching" based on user-selected priorities. The entire system was built for scale using event-driven archi

Automotive Media API & Vehicle Comp

13938439
I built several interconnected components inside a unified AI chatbot SaaS platform designed to automate complex workflows across multiple industries. One of the core modules is an EV diagnostic system that allows users to select their vehicle, describe symptoms or enter error codes, upload photos, and receive an AI‑generated diagnosis with severity, probable causes and recommended next steps. The system also connects to a product and service catalog, enabling the assistant to suggest compatible accessories such as chargers, cables, auxiliary batteries, boosters, wallbox installations and safety equipment. The entire flow is multilingual, available 24/7 and optimized for natural‑language interaction. I also developed the voice automation layer of the platform, integrating real‑time call logs, cost tracking, call‑end reasons, timestamps and assistant performance metrics. This module supports AI voice agents used for support, claims and customer operations, giving teams full visibility

AI Chatbot SaaS Platform EV Diagnose

I built several interconnected components inside a unified AI chatbot SaaS platform designed to automate complex workflows across multiple industries. One of the core modules is an EV diagnostic system that allows users to select their vehicle, describe symptoms or enter error codes, upload photos, and receive an AI‑generated diagnosis with severity, probable causes and recommended next steps. The system also connects to a product and service catalog, enabling the assistant to suggest compatible accessories such as chargers, cables, auxiliary batteries, boosters, wallbox installations and safety equipment. The entire flow is multilingual, available 24/7 and optimized for natural‑language interaction. I also developed the voice automation layer of the platform, integrating real‑time call logs, cost tracking, call‑end reasons, timestamps and assistant performance metrics. This module supports AI voice agents used for support, claims and customer operations, giving teams full visibility

AI Chatbot SaaS Platform EV Diagnose

I built several interconnected components inside a unified AI chatbot SaaS platform designed to automate complex workflows across multiple industries. One of the core modules is an EV diagnostic system that allows users to select their vehicle, describe symptoms or enter error codes, upload photos, and receive an AI‑generated diagnosis with severity, probable causes and recommended next steps. The system also connects to a product and service catalog, enabling the assistant to suggest compatible accessories such as chargers, cables, auxiliary batteries, boosters, wallbox installations and safety equipment. The entire flow is multilingual, available 24/7 and optimized for natural‑language interaction. I also developed the voice automation layer of the platform, integrating real‑time call logs, cost tracking, call‑end reasons, timestamps and assistant performance metrics. This module supports AI voice agents used for support, claims and customer operations, giving teams full visibility

AI Chatbot SaaS Platform EV Diagnose

I built several interconnected components inside a unified AI chatbot SaaS platform designed to automate complex workflows across multiple industries. One of the core modules is an EV diagnostic system that allows users to select their vehicle, describe symptoms or enter error codes, upload photos, and receive an AI‑generated diagnosis with severity, probable causes and recommended next steps. The system also connects to a product and service catalog, enabling the assistant to suggest compatible accessories such as chargers, cables, auxiliary batteries, boosters, wallbox installations and safety equipment. The entire flow is multilingual, available 24/7 and optimized for natural‑language interaction. I also developed the voice automation layer of the platform, integrating real‑time call logs, cost tracking, call‑end reasons, timestamps and assistant performance metrics. This module supports AI voice agents used for support, claims and customer operations, giving teams full visibility

AI Chatbot SaaS Platform EV Diagnose

13938432
I contributed multiple modules to a full AI Chatbot SaaS platform designed to automate communication, operations, and customer workflows across different industries. 1. AI Voice Automation (VAPI Call Logs & Monitoring) I implemented the call‑tracking and analytics layer for the platform’s voice AI system. This includes real‑time logs for outbound calls, showing call IDs, assistant identity, customer numbers, call type, end reason, timestamps, duration, and cost. This module integrates directly with the platform’s Assistants, Squads, Tools, Phone Numbers, Metrics, and API Keys, giving operators full visibility into AI‑driven conversations. 2. Claims Automation – Insurance Company Management I built the company‑management dashboard used in the platform’s automated claims workflow. Operators can sync phone numbers, add/edit insurers, manage working windows, and toggle active/paused states. This module powers automated ticket routing and AI‑driven communication with insurance com

AI Chatbot SaaS Platform

I contributed multiple modules to a full AI Chatbot SaaS platform designed to automate communication, operations, and customer workflows across different industries. 1. AI Voice Automation (VAPI Call Logs & Monitoring) I implemented the call‑tracking and analytics layer for the platform’s voice AI system. This includes real‑time logs for outbound calls, showing call IDs, assistant identity, customer numbers, call type, end reason, timestamps, duration, and cost. This module integrates directly with the platform’s Assistants, Squads, Tools, Phone Numbers, Metrics, and API Keys, giving operators full visibility into AI‑driven conversations. 2. Claims Automation – Insurance Company Management I built the company‑management dashboard used in the platform’s automated claims workflow. Operators can sync phone numbers, add/edit insurers, manage working windows, and toggle active/paused states. This module powers automated ticket routing and AI‑driven communication with insurance com

AI Chatbot SaaS Platform

13938422
I developed and integrated two operational modules for an AI‑driven communication and claims‑processing system. 1. VAPI Call Logs & Monitoring Module I implemented a real‑time call analytics dashboard that displays outbound AI‑assistant calls, including call ID, assistant identity, customer number, call type, end reason, timestamps, duration, and cost. The system supports detailed monitoring for each call, enabling teams to audit performance, detect issues (e.g., silence, customer hang‑ups), and optimize assistant behavior. The module is fully integrated with VAPI’s Assistants, Squads, Tools, Phone Numbers, Metrics, and API Keys sections, ensuring seamless observability across the entire voice automation pipeline. 2. Claims Automation – Insurance Company Management I built a management interface for insurance companies used in automated claims workflows. The dashboard allows syncing phone numbers from tickets, adding/editing companies, managing working windows, and toggling a

AI Call Automation & Claims Manageme

I developed and integrated two operational modules for an AI‑driven communication and claims‑processing system. 1. VAPI Call Logs & Monitoring Module I implemented a real‑time call analytics dashboard that displays outbound AI‑assistant calls, including call ID, assistant identity, customer number, call type, end reason, timestamps, duration, and cost. The system supports detailed monitoring for each call, enabling teams to audit performance, detect issues (e.g., silence, customer hang‑ups), and optimize assistant behavior. The module is fully integrated with VAPI’s Assistants, Squads, Tools, Phone Numbers, Metrics, and API Keys sections, ensuring seamless observability across the entire voice automation pipeline. 2. Claims Automation – Insurance Company Management I built a management interface for insurance companies used in automated claims workflows. The dashboard allows syncing phone numbers from tickets, adding/editing companies, managing working windows, and toggling a

AI Call Automation & Claims Manageme

I developed and integrated two operational modules for an AI‑driven communication and claims‑processing system. 1. VAPI Call Logs & Monitoring Module I implemented a real‑time call analytics dashboard that displays outbound AI‑assistant calls, including call ID, assistant identity, customer number, call type, end reason, timestamps, duration, and cost. The system supports detailed monitoring for each call, enabling teams to audit performance, detect issues (e.g., silence, customer hang‑ups), and optimize assistant behavior. The module is fully integrated with VAPI’s Assistants, Squads, Tools, Phone Numbers, Metrics, and API Keys sections, ensuring seamless observability across the entire voice automation pipeline. 2. Claims Automation – Insurance Company Management I built a management interface for insurance companies used in automated claims workflows. The dashboard allows syncing phone numbers from tickets, adding/editing companies, managing working windows, and toggling a

AI Call Automation & Claims Manageme

I developed and integrated two operational modules for an AI‑driven communication and claims‑processing system. 1. VAPI Call Logs & Monitoring Module I implemented a real‑time call analytics dashboard that displays outbound AI‑assistant calls, including call ID, assistant identity, customer number, call type, end reason, timestamps, duration, and cost. The system supports detailed monitoring for each call, enabling teams to audit performance, detect issues (e.g., silence, customer hang‑ups), and optimize assistant behavior. The module is fully integrated with VAPI’s Assistants, Squads, Tools, Phone Numbers, Metrics, and API Keys sections, ensuring seamless observability across the entire voice automation pipeline. 2. Claims Automation – Insurance Company Management I built a management interface for insurance companies used in automated claims workflows. The dashboard allows syncing phone numbers from tickets, adding/editing companies, managing working windows, and toggling a

AI Call Automation & Claims Manageme

13793797
Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

13949380
designed and implemented a mobile solution that transforms traditional paper forms into fully interactive smart mobile forms. The project included creating digital versions of work orders, jobsite inspections, and field reports with support for images, sketches, maps, and digital signatures. The interface was optimized for field technicians, enabling fast data entry, photo capture, and real‑time syncing. The system also integrates with external business applications, allowing automated workflows, centralized data storage, and improved operational efficiency.

Digital Work Orders & Inspection

13793671
ngineered a high-performance automotive data platform that aggregates, normalizes, and serves structured vehicle data from top-tier sources like Car and Driver. The system featured a multi-source orchestration layer (Apache Airflow) managing Python-based collectors that processed detailed review texts, performance specs (0-60 mph, MPG), expert ratings, and pricing from HTML, PDFs (road test sheets), and RSS feeds. Data was cleansed, deduplicated, and stored in a time-series optimized PostgreSQL database. The core was a low-latency GraphQL API (Apollo Server/Node.js) allowing complex queries (e.g., "find all SUVs with >300 hp and a Car and Driver rating >8/10"). The consumer-facing frontend (Next.js 14, App Router) was a dynamic comparison tool with side-by-side spec sheets, interactive data visualizations of performance metrics, and personalized "vehicle matching" based on user-selected priorities. The entire system was built for scale using event-driven archi

Automotive Media API & Vehicle Comp

ngineered a high-performance automotive data platform that aggregates, normalizes, and serves structured vehicle data from top-tier sources like Car and Driver. The system featured a multi-source orchestration layer (Apache Airflow) managing Python-based collectors that processed detailed review texts, performance specs (0-60 mph, MPG), expert ratings, and pricing from HTML, PDFs (road test sheets), and RSS feeds. Data was cleansed, deduplicated, and stored in a time-series optimized PostgreSQL database. The core was a low-latency GraphQL API (Apollo Server/Node.js) allowing complex queries (e.g., "find all SUVs with >300 hp and a Car and Driver rating >8/10"). The consumer-facing frontend (Next.js 14, App Router) was a dynamic comparison tool with side-by-side spec sheets, interactive data visualizations of performance metrics, and personalized "vehicle matching" based on user-selected priorities. The entire system was built for scale using event-driven archi

Automotive Media API & Vehicle Comp

ngineered a high-performance automotive data platform that aggregates, normalizes, and serves structured vehicle data from top-tier sources like Car and Driver. The system featured a multi-source orchestration layer (Apache Airflow) managing Python-based collectors that processed detailed review texts, performance specs (0-60 mph, MPG), expert ratings, and pricing from HTML, PDFs (road test sheets), and RSS feeds. Data was cleansed, deduplicated, and stored in a time-series optimized PostgreSQL database. The core was a low-latency GraphQL API (Apollo Server/Node.js) allowing complex queries (e.g., "find all SUVs with >300 hp and a Car and Driver rating >8/10"). The consumer-facing frontend (Next.js 14, App Router) was a dynamic comparison tool with side-by-side spec sheets, interactive data visualizations of performance metrics, and personalized "vehicle matching" based on user-selected priorities. The entire system was built for scale using event-driven archi

Automotive Media API & Vehicle Comp

13938439
I built several interconnected components inside a unified AI chatbot SaaS platform designed to automate complex workflows across multiple industries. One of the core modules is an EV diagnostic system that allows users to select their vehicle, describe symptoms or enter error codes, upload photos, and receive an AI‑generated diagnosis with severity, probable causes and recommended next steps. The system also connects to a product and service catalog, enabling the assistant to suggest compatible accessories such as chargers, cables, auxiliary batteries, boosters, wallbox installations and safety equipment. The entire flow is multilingual, available 24/7 and optimized for natural‑language interaction. I also developed the voice automation layer of the platform, integrating real‑time call logs, cost tracking, call‑end reasons, timestamps and assistant performance metrics. This module supports AI voice agents used for support, claims and customer operations, giving teams full visibility

AI Chatbot SaaS Platform EV Diagnose

I built several interconnected components inside a unified AI chatbot SaaS platform designed to automate complex workflows across multiple industries. One of the core modules is an EV diagnostic system that allows users to select their vehicle, describe symptoms or enter error codes, upload photos, and receive an AI‑generated diagnosis with severity, probable causes and recommended next steps. The system also connects to a product and service catalog, enabling the assistant to suggest compatible accessories such as chargers, cables, auxiliary batteries, boosters, wallbox installations and safety equipment. The entire flow is multilingual, available 24/7 and optimized for natural‑language interaction. I also developed the voice automation layer of the platform, integrating real‑time call logs, cost tracking, call‑end reasons, timestamps and assistant performance metrics. This module supports AI voice agents used for support, claims and customer operations, giving teams full visibility

AI Chatbot SaaS Platform EV Diagnose

I built several interconnected components inside a unified AI chatbot SaaS platform designed to automate complex workflows across multiple industries. One of the core modules is an EV diagnostic system that allows users to select their vehicle, describe symptoms or enter error codes, upload photos, and receive an AI‑generated diagnosis with severity, probable causes and recommended next steps. The system also connects to a product and service catalog, enabling the assistant to suggest compatible accessories such as chargers, cables, auxiliary batteries, boosters, wallbox installations and safety equipment. The entire flow is multilingual, available 24/7 and optimized for natural‑language interaction. I also developed the voice automation layer of the platform, integrating real‑time call logs, cost tracking, call‑end reasons, timestamps and assistant performance metrics. This module supports AI voice agents used for support, claims and customer operations, giving teams full visibility

AI Chatbot SaaS Platform EV Diagnose

I built several interconnected components inside a unified AI chatbot SaaS platform designed to automate complex workflows across multiple industries. One of the core modules is an EV diagnostic system that allows users to select their vehicle, describe symptoms or enter error codes, upload photos, and receive an AI‑generated diagnosis with severity, probable causes and recommended next steps. The system also connects to a product and service catalog, enabling the assistant to suggest compatible accessories such as chargers, cables, auxiliary batteries, boosters, wallbox installations and safety equipment. The entire flow is multilingual, available 24/7 and optimized for natural‑language interaction. I also developed the voice automation layer of the platform, integrating real‑time call logs, cost tracking, call‑end reasons, timestamps and assistant performance metrics. This module supports AI voice agents used for support, claims and customer operations, giving teams full visibility

AI Chatbot SaaS Platform EV Diagnose

13938432
I contributed multiple modules to a full AI Chatbot SaaS platform designed to automate communication, operations, and customer workflows across different industries. 1. AI Voice Automation (VAPI Call Logs & Monitoring) I implemented the call‑tracking and analytics layer for the platform’s voice AI system. This includes real‑time logs for outbound calls, showing call IDs, assistant identity, customer numbers, call type, end reason, timestamps, duration, and cost. This module integrates directly with the platform’s Assistants, Squads, Tools, Phone Numbers, Metrics, and API Keys, giving operators full visibility into AI‑driven conversations. 2. Claims Automation – Insurance Company Management I built the company‑management dashboard used in the platform’s automated claims workflow. Operators can sync phone numbers, add/edit insurers, manage working windows, and toggle active/paused states. This module powers automated ticket routing and AI‑driven communication with insurance com

AI Chatbot SaaS Platform

I contributed multiple modules to a full AI Chatbot SaaS platform designed to automate communication, operations, and customer workflows across different industries. 1. AI Voice Automation (VAPI Call Logs & Monitoring) I implemented the call‑tracking and analytics layer for the platform’s voice AI system. This includes real‑time logs for outbound calls, showing call IDs, assistant identity, customer numbers, call type, end reason, timestamps, duration, and cost. This module integrates directly with the platform’s Assistants, Squads, Tools, Phone Numbers, Metrics, and API Keys, giving operators full visibility into AI‑driven conversations. 2. Claims Automation – Insurance Company Management I built the company‑management dashboard used in the platform’s automated claims workflow. Operators can sync phone numbers, add/edit insurers, manage working windows, and toggle active/paused states. This module powers automated ticket routing and AI‑driven communication with insurance com

AI Chatbot SaaS Platform

13938422
I developed and integrated two operational modules for an AI‑driven communication and claims‑processing system. 1. VAPI Call Logs & Monitoring Module I implemented a real‑time call analytics dashboard that displays outbound AI‑assistant calls, including call ID, assistant identity, customer number, call type, end reason, timestamps, duration, and cost. The system supports detailed monitoring for each call, enabling teams to audit performance, detect issues (e.g., silence, customer hang‑ups), and optimize assistant behavior. The module is fully integrated with VAPI’s Assistants, Squads, Tools, Phone Numbers, Metrics, and API Keys sections, ensuring seamless observability across the entire voice automation pipeline. 2. Claims Automation – Insurance Company Management I built a management interface for insurance companies used in automated claims workflows. The dashboard allows syncing phone numbers from tickets, adding/editing companies, managing working windows, and toggling a

AI Call Automation & Claims Manageme

I developed and integrated two operational modules for an AI‑driven communication and claims‑processing system. 1. VAPI Call Logs & Monitoring Module I implemented a real‑time call analytics dashboard that displays outbound AI‑assistant calls, including call ID, assistant identity, customer number, call type, end reason, timestamps, duration, and cost. The system supports detailed monitoring for each call, enabling teams to audit performance, detect issues (e.g., silence, customer hang‑ups), and optimize assistant behavior. The module is fully integrated with VAPI’s Assistants, Squads, Tools, Phone Numbers, Metrics, and API Keys sections, ensuring seamless observability across the entire voice automation pipeline. 2. Claims Automation – Insurance Company Management I built a management interface for insurance companies used in automated claims workflows. The dashboard allows syncing phone numbers from tickets, adding/editing companies, managing working windows, and toggling a

AI Call Automation & Claims Manageme

I developed and integrated two operational modules for an AI‑driven communication and claims‑processing system. 1. VAPI Call Logs & Monitoring Module I implemented a real‑time call analytics dashboard that displays outbound AI‑assistant calls, including call ID, assistant identity, customer number, call type, end reason, timestamps, duration, and cost. The system supports detailed monitoring for each call, enabling teams to audit performance, detect issues (e.g., silence, customer hang‑ups), and optimize assistant behavior. The module is fully integrated with VAPI’s Assistants, Squads, Tools, Phone Numbers, Metrics, and API Keys sections, ensuring seamless observability across the entire voice automation pipeline. 2. Claims Automation – Insurance Company Management I built a management interface for insurance companies used in automated claims workflows. The dashboard allows syncing phone numbers from tickets, adding/editing companies, managing working windows, and toggling a

AI Call Automation & Claims Manageme

I developed and integrated two operational modules for an AI‑driven communication and claims‑processing system. 1. VAPI Call Logs & Monitoring Module I implemented a real‑time call analytics dashboard that displays outbound AI‑assistant calls, including call ID, assistant identity, customer number, call type, end reason, timestamps, duration, and cost. The system supports detailed monitoring for each call, enabling teams to audit performance, detect issues (e.g., silence, customer hang‑ups), and optimize assistant behavior. The module is fully integrated with VAPI’s Assistants, Squads, Tools, Phone Numbers, Metrics, and API Keys sections, ensuring seamless observability across the entire voice automation pipeline. 2. Claims Automation – Insurance Company Management I built a management interface for insurance companies used in automated claims workflows. The dashboard allows syncing phone numbers from tickets, adding/editing companies, managing working windows, and toggling a

AI Call Automation & Claims Manageme

13793797
Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

13949380
designed and implemented a mobile solution that transforms traditional paper forms into fully interactive smart mobile forms. The project included creating digital versions of work orders, jobsite inspections, and field reports with support for images, sketches, maps, and digital signatures. The interface was optimized for field technicians, enabling fast data entry, photo capture, and real‑time syncing. The system also integrates with external business applications, allowing automated workflows, centralized data storage, and improved operational efficiency.

Digital Work Orders & Inspection

4.8 · 22 Reviews
22 Reviews
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Flag of SPAIN

Michael

4.8

€400 EUR

3 hours ago

WhatsApp & Spoki Lead Qualification System

Very good planning and execution

CRM
ERP
Freelancer API
Microsoft Office
Artificial Intelligence

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Fidel

5.0

$200 USD

16 days ago

Bot- doordash

Juan was fantastic to work with from start to finish. He clearly knew what he was doing, communicated clearly throughout the project, and delivered high-quality work on time and within budget. He was professional, responsive, and easy to collaborate with. I'd definitely hire him again for future projects and would recommend him to anyone looking for reliable, skilled work.

PHP
Python
Software Architecture
Natural Language Processing

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Andrew

5.0

$250 AUD

27 days ago

AI-Driven Ecommerce & Booking Website

responds and reflects quickly to ongoing development opportunties and solution based results

PHP
Website Design
eCommerce
HTML
Chatbot

+3 more

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Jose Jorge

2.0

$900 USD

1 month ago

Desarrollador PHP/MySQL para debugging profundo de CRM en español: saldos, pagos, comisiones y reportes -- 2

tiene conocimientos, tiene exptertise, pero no se le da la gana de contestarte, ni de seguir la ruta de trabajo plaenada. comete errores y quiere culparte luego, tiene pésima comunicación. hay mejores opciones en la plataforma sin duda alguna

PHP
Engineering
SQL
Software Architecture
CRM

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Andrew

5.0

$2,960 AUD

2 months ago

Quote & Booking Bot Setup

Understands scope of project and delivers in a timely and professional manner. [04 August, 2026] prompt professional and makes ammendments when recieved feedback super quick

PHP
JavaScript
Software Architecture
MySQL
Automation

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Experience

Senior Software engineerav

May, 2021 - Feb, 2026

•

4 years, 9 months

Stratech Corp

May, 2021 - Feb, 2026

•

4 years, 9 months

• Designed and developed machine learning models using Python (scikit-learn, TensorFlow, PyTorch) to support predictive analytics and automation initiatives • Engineered scalable data pipelines using Python and FastAPI, enabling efficient data ingestion, preprocessing, and feature engineering • Deployed and managed production-grade ML models using FastAPI, AWS, and Azure, supporting both real-time and batch inference

Flag of CHILE

Snatiago, Chile

May, 2021 - Feb, 2026

•

4 years, 9 months

Senior Full Stack Engineer

Mar, 2016 - May, 2021

•

5 years, 2 months

artool

Mar, 2016 - May, 2021

•

5 years, 2 months

• Developed and maintained scalable backend services using Node.js, Python (Django, FastAPI), PHP, and Golang • Designed and implemented RESTful APIs to support frontend applications and third-party integrations • Built responsive and dynamic frontend applications using React, Angular, JavaScript, HTML, and CSS • Designed and optimized databases including PostgreSQL, MySQL, and MongoDB • Integrated third-party APIs and external services to enhance application capabilities

Flag of CHILE

santiago, Chile

Mar, 2016 - May, 2021

•

5 years, 2 months

Full Stack Developer

Feb, 2014 - Feb, 2016

•

2 years

Neotel

Feb, 2014 - Feb, 2016

•

2 years

• Developed full stack web applications using React, Angular, Node.js, and Python-based services • Built reusable and maintainable frontend components with a focus on performance and scalability • Designed and integrated backend APIs to support application features and business logic • Optimized application performance using techniques such as lazy loading, efficient state management, and code splitting • Collaborated with UI/UX designers and backend engineers to ensure seamless user experiences

Flag of CHILE

Santiago, Chile

Feb, 2014 - Feb, 2016

•

2 years

Education

Universidad San Sebastián

2009 - 2013

•

4 years

bachelor's degree

Flag of CHILE

Chile

2009 - 2013

•

4 years

Certifications

P

Preferred Freelancer Program SLA

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