AI Support Chatbot Deployment

@joomextensions

Hi, We've built AI chatbot integrations for both web and Flutter mobile apps — this project is well within our wheelhouse. Our approach for your requirements: - Stack: Dialogflow CX (or LLM-based) + JS widget for web + REST API for mobile - Knowledge Base: No-code FAQ editor — your team updates it without touching code - Live Handoff: Confidence-threshold based, integrates with Intercom/Freshdesk/Zendesk - Analytics: Volume, resolution rate, missed intents — built in from Day 1 **Your acceptance criteria:** 90%+ intent accuracy via iterative training on your test set <2 sec latency via optimized webhook deployment 95%+ handoff accuracy via rule + confidence triggers Full Git repo with docs, flows, and integration code Timeline: 3-5 weeks Delivery: Phased, with testing and sign-off at each stage We are Harmis Technology — 275+ reviews, 4.8★, on Freelancer since 2009. 95% on-budget track record. Quick question: What live support tool are you currently using (Intercom, Zendesk, custom)? This helps me finalize the quote accurately.

@n2rtechnologies

Hi there, I reviewed your requirements and this is exactly the kind of project we handle well. I noticed you need 24/7 support across website and mobile — that's a solid scope that requires clean architecture and reliable integrations. I have a couple of questions about your expected chat volume and whether you're leaning toward a specific ML framework. Happy to jump on a quick call to discuss. I have delivered 1500+ web and mobile projects over 14+ years — happy to share relevant examples. Thanks, Hasan

@ZohaibRoy

⭐⭐⭐⭐⭐ Create an AI Chatbot for 24/7 Customer Support on Website & Mobile App ❇️ Hi My Friend, I hope you are doing well. I just reviewed your project requirements and see you are looking for an AI-driven chatbot for customer support. You don’t need to look any further; Zohaib is here to help you! My team has successfully handled 50+ similar projects in chatbot development. I will design, train, and deploy a model that understands your products and policies, ensuring it responds accurately and quickly. ➡️ Why Me? I can easily create your AI chatbot as I have 5 years of experience in chatbot development, specializing in customer support solutions. My skills include AI model training, JavaScript integration, and analytics setup. I also have a strong grip on frameworks like Dialogflow and Rasa, ensuring I can meet your project needs effectively. ➡️ Let's have a quick chat to discuss your project in detail and let me show you samples of my previous work. Looking forward to discussing this with you in chat. ➡️ Skills & Experience: ✅ AI Model Training ✅ Chatbot Development ✅ JavaScript Integration ✅ REST API Development ✅ Knowledge Base Management ✅ Customer Support Solutions ✅ Analytics Setup ✅ Intent Recognition ✅ Troubleshooting Guidance ✅ User Experience Design ✅ Frameworks: Dialogflow, Rasa ✅ Mobile App Integration Waiting for your response! Best Regards, Zohaib

@softsolution2000

I am confident that my skills in Java, JavaScript, Mobile App Development, Android, and Machine Learning (ML) are a great match for the AI Support Chatbot Deployment project. I have experience deploying similar solutions using Dialogflow and Rasa, ensuring high intent recognition accuracy and seamless handoff to live agents. My preferred stack includes Dialogflow for NLP and JavaScript for web integration. I am eager to discuss the project scope to adjust the budget accordingly and prioritize your requirements. Let's start this project and deliver exceptional customer support together. Please go through my profile its 15 years old see the work I did over the years. No Win No Fee means that your satisfaction is my utmost priority. Lets discuss the job details. Moreover, I am willing to start the job and perform tasks without even being hired; it is just to show my commitment to this project. Looking forward to hear from you.

@kamran2012

Hi, I will build and deploy your AI support chatbot for both website and mobile app — trained on your product range, policies, and tone of voice, with an updatable knowledge base your team can manage without code. The bot will handle greetings, FAQs, troubleshooting flows, and hand off to a live agent when needed. Analytics dashboard covering conversation volume, resolution rates, and missed intents included. I would go with Rasa for this — it runs self-hosted so your customer data stays on your infrastructure, and it gives you full control over the NLU pipeline to hit that 90%+ intent accuracy. For the knowledge base updates, I will build a simple admin interface where your team adds Q&A pairs that retrain the model automatically without touching any code or config files. Questions: 1) How will the live agent handoff work — do you use a helpdesk tool like Zendesk, Freshdesk, or an in-house system? 2) Roughly how many FAQ topics and troubleshooting flows should the bot cover at launch? Looking forward to your response. Best regards, Kamran

@Srashtasoft

A Warm Hello! I can build your AI-driven support chatbot end-to-end—trained on your products, policies, and tone, deployed across web and mobile, and equipped with a fully maintainable knowledge base. I’ve delivered similar multi-platform bots with high intent accuracy, fast response times, and smooth human-agent handoff. My proposed stack: Dialogflow CX or Rasa with a lightweight LLM layer for improved understanding, deployed behind a fast API gateway to guarantee <2s latency. Web integration via JS widget; mobile integration via SDK/REST. A simple, non-technical FAQ/KB editor will let your team update content anytime. Analytics will track intent success, resolutions, and missed queries. Scope I’ll deliver: Training data + model tuned for 90%+ intent accuracy on your test set. Web + mobile chatbot UI with handoff triggers working >95% reliability. Knowledge base CMS for easy updates. Git repo with integration code, flows, and deployment guide. A couple of questions: Do you already use a live-chat provider for agent handoff (Freshchat, Zendesk, Intercom)? Should the chatbot also manage authenticated user actions (orders, tickets), or just general support? Timeline: approx. 3–5 weeks depending on training depth. Let’s set up a quick call to discuss things better. Let’s discuss it more in chat. Best Regards, Jemin Sagar

@arbu1499

Hi! I understand you need an AI chatbot that can handle support end-to-end—accurate intent recognition, fast responses (<2s), and reliable human handoff—across both web and mobile. I’ve worked on similar chatbot systems where the focus was on structured intent training, fallback handling, and seamless SDK/API integrations. My approach would use Dialogflow CX or a custom LLM + retrieval (RAG) with a managed knowledge base, ensuring your team can update FAQs without code. I’ll integrate via JS widget for web + REST/SDK for mobile, add analytics (intents, resolution, drop-offs), and implement smart escalation triggers for agents. Timeline: 2–3 weeks for a fully functional, tested deployment with Git-based handoff. Looking forward for your positive response in the chatbox. Best Regards, Arbaz N

@iosifpeterfi

I'm Iosif Peterfi, 15+ years delivering secure, scalable tech solutions for web and mobile. This is my speciality: turning customer support needs into AI-driven experiences that understand your product, policies, and brand voice, then scale without code changes. You need an AI chatbot that works 24/7 on your website and mobile app, greets visitors, answers common questions, guides troubleshooting, and hands off complex cases to a live agent in English. It must embed on site via a widget and be accessible in the mobile app through a SDK or REST API, with an easy-to-update knowledge base and basic analytics, plus reliable escalation when needed. I'll architect a product-aware bot, train it on your product range and policies, deploy across both platforms, and provide a simple content editor so your team can add FAQs without engineering touch. Outcomes: improved customer satisfaction, faster first-contact resolution, and reduced live-agent load. Deliverables: a deployable bot, web widget, mobile integration bridge, knowledge-base editor, analytics, and complete docs. Risks are mitigated by tested intents, fallbacks, and clear handoff rules, with ongoing monitoring. Last quarter I helped a consumer electronics retailer deploy an AI chat assistant for their support site and mobile app. They achieved 92% intent recognition and 1.8s average response time, cutting escalations by 40%. Let's chat - I can walk you through my approach in 15 minutes.

@ixorawebmob

Hello, I’ve gone through your project details and this is something I can definitely help you with. With my 10+ years of experience in mobile and web app development, I specialize in building AI-driven solutions that enhance customer engagement. I’ll architect, train, and deploy a chatbot that can effectively serve your customers 24/7 by greeting them, resolving common queries, and smoothly transferring complex issues to live agents. I ensure a robust implementation by selecting proven frameworks like Dialogflow or Rasa, focusing on scalability and seamless integration for both your website and mobile app. My approach will also include an easily updatable knowledge base for your team, plus basic analytics to track performance. 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: 1. What is your preferred timeline for these deployments? 2. Do you have a specific framework in mind or are you open to suggestions? 3. How do you envision the handoff process to human agents? Let’s discuss over chat! What is your preferred timeline for these deployments? Regards, Arpit Jaiswal

@GameOfWords

As an established developer with a deep-seated interest in AI, I believe I'm the right fit for this project. My extensive experience in AI Chatbot Development and Mobile App Development, specifically using technologies like React Native, Node.js, and Java will be paramount in deploying a solution that is both smart and efficient. In particular, my understanding of various proven frameworks like Dialogflow, Rasa and Microsoft Bot Framework enable me to choose the best stack for your specific needs. Additionally, my familiarity with LLM integrations such as OpenAI brings a level of customization which can cater to your exact requirements. Finally, aside from my technical skills, I also bring to the table my proficiency in Business Writing - an advantage that would ensure all necessary knowledge base tools for updating FAQs without code involvement are thoroughly communicated. In addition to tailoring content, this expertise extends to properly documenting projects in a Git repo. By choosing me for your project, you're getting end-to-end service delivery that's reliable and professionally done.

@webmasters486

Hi, I can build an AI-driven chatbot for your website and mobile app that handles customer support 24/7, greeting visitors, answering FAQs, guiding troubleshooting, and escalating complex cases to live agents. The bot will be trained to understand your products, policies, and tone of voice, delivering accurate, natural, and responsive interactions while maintaining English-language precision. I recommend using a proven framework such as Dialogflow, Rasa, or a custom LLM solution, integrated via a JavaScript widget for the website and REST API or SDK for the mobile app. A simple knowledge base will allow your team to update FAQs without code. The system will include analytics tracking conversation volume, resolution rates, and missed intents, ensuring continuous improvement and high performance. You’ll receive a fully functional bot with 90%+ intent recognition accuracy, <2 seconds response time, and reliable human handoff in >95% of flagged cases. Complete source code, flows, training data, integration instructions, and documentation will be delivered in a Git repo for seamless handover and future maintenance. Best regards, Muhammad Adil Portfolio: https://www.freelancer.com/u/webmasters486

@abhishekchouras6

With your AI Support Chatbot Deployment project, my skills as a mobile app developer with expertise in Flutter and Android development align perfectly. I understand the importance of creating not just functional, but aesthetically pleasing applications that enhance the user experience. Incorporating a conversational chatbot on both your website and mobile app will be seamless using my knowledge and experience. Throughout my career, I have become well-versed in various programming languages, including Java and Kotlin, equipping me with the ability to build robust and scalable applications. This strength, combined with my prior experience deploying similar AI-driven chatbots, will enable me to architect, train, and deploy the necessary model, tailoring it precisely to your product range and tone of voice. Furthermore, I recognize that continuous improvement is essential. In that regard, I will design an easy-to-update knowledge base for your team's convenience without disrupting any codebase. My efficient working style and proficiency in maintaining existing applications also ensure smooth implementation of necessary analytics for you to tangibly measure conversation volume, resolution rates, and missed intents. To optimize collaboration, I'll provide comprehensive installation instructions together with the source in a Git repo. Choose me for this project, and together we'll create a highly efficient AI support system for your customers that exceeds all expectations.

@avinashdubeyg209

Noticed you're looking to deploy a comprehensive AI chatbot for customer support on both web and mobile platforms. Recently built a chatbot for a health tech firm, meeting similar requirements by integrating with their existing systems for seamless handoff to human agents. Curious if you're considering a specific NLP framework, like Rasa or Dialogflow, for natural language processing? This could impact user interaction quality significantly. Let me know if you’d like to explore potential approaches or start with a quick plan.

@SmartCodeDev

Hello, I can build and deploy a reliable AI chatbot that meets your accuracy, latency, and handoff requirements across web and mobile. I’d use a hybrid approach (Rasa or lightweight LLM + retrieval) to ensure high intent accuracy while keeping responses fast and controllable. The system will include a structured knowledge base your team can update easily, with versioned training data and no-code FAQ management. I’ll integrate the bot via a web widget and REST/SDK endpoints for your mobile app, ensuring consistent behavior across both platforms. Human handoff will be rule-based + confidence-driven to hit the >95% trigger requirement, with fallback safeguards to avoid bad responses. Analytics will track conversations, resolution rates, and missed intents through a simple dashboard. I’ll deliver full source code, flows, training data, and setup instructions in a clean Git repo.

@Ekarthaan

Hi Abdul N., This is quite similar to a project I delivered last week, so I can jump straight into execution. Ready to start immediately. 1) Which live‑agent platform should receive handoffs (Zendesk, Intercom, Salesforce, or custom), and what ticket fields/metadata must be passed? 2) Is your mobile app native (iOS/Android) or React Native/Flutter, and do you prefer an SDK widget or a REST API with an in‑app UI? Suggestion 1: Hybrid NLU—Rasa intent classifier fine‑tuned on your set + RAG over a versioned KB (pgvector/Elastic) for long‑tail FAQs; calibrated thresholds for safe escalation. Suggestion 2: Design for p95<2s with a stateless FastAPI service, Redis caching, token streaming, and K8s autoscaling with OTel/Prometheus. Preferred stack: Rasa OSS + FastAPI + Postgres/pgvector + Redis; web widget + mobile REST; AWS/GCP. Action Plan: W1 discovery, content intake, intents/KPIs. W2 editable KB (Markdown/CMS) + embedding sync; train/evaluate NLU to ≥90% on your test set. W3 dialog flows, guardrails, and handoff integration. W4 website widget + mobile REST; analytics (volume, resolution, missed intents). W5 load tests, latency tuning to p95<2s; acceptance checks incl. >95% handoff trigger. W6 docs, Git repo (flows, data, code), install guide, handover. Best Regards, Sid

@humanspdy

Hello, I can develop an AI-powered chatbot for your website and mobile app that handles customer support, answers FAQs, assists with troubleshooting, and smoothly transfers complex cases to a live agent. The bot will be trained on your product information and policies, with fast response times and high intent accuracy. I will integrate the chatbot using a scalable framework such as Dialogflow or a custom LLM solution, provide an easy-to-update knowledge base for your team, and include analytics for conversations and performance tracking. I can also deliver full documentation and Git repository for deployment and future updates. Warm regards, Vikas

@NEHABHAT92

With over 9+ years of experience in web and mobile app development, Particularly in Android, JavaScript and Mobile App Development , my team and I have built and deployed numerous successful AI-based systems for a wide range of clients. Our focus on quality, precision, and meeting project goals positions us as suitable contenders for your AI Support Chatbot Deployment. In terms of the project's scope, we can effectively architect, train and deploy a chatbot for your website and mobile app using proven platforms like Dialogflow or Rasa as per your request. Additionally, our expertise in JavaScript will enable us to seamlessly embed the chat interface and provide easy-to-update knowledge base functionalities that you require. We understand the value of effective analytics; thus ensuring we would provide the conversation volume, resolution rates and missed intents metrics you need. As for the acceptance criteria mentioned, we pride ourselves in delivering exceptional accuracy, minimal latency along with correct handoff rates; all which we can guarantee. To ensure complete transparency and customer satisfaction, we correctly deliver detailed installations instructions & source code on Git repo. Finally from a cost perspective, while we ensure effective cost of project enablement we do not compromise on the quality of work. To sum up, choosing me ensures a seamless implementation of an efficient AI Support Chatbot on both your webstie and app. I look forward to disc

@waqaswebmaster

Hi there, The risk with AI Support Deployment is "Hallucination and Loop-Trap." If the bot isn't grounded in a strict Knowledge Base (RAG), it will invent policies or trap users in repetitive loops, damaging your brand's trust. I focus on Deterministic Guardrails to ensure 90%+ intent accuracy while maintaining a human-like tone. My Micro-Strategy for your AI Chatbot: The Tech Stack: I recommend a Hybrid RAG Approach (Retrieval-Augmented Generation) using OpenAI’s GPT-4o API or Anthropic Claude via LangChain. This ensures the bot only answers based on your specific product range and policies. Ultra-Low Latency: To meet your <2s response goal, I’ll implement a Streaming Response architecture on the frontend and an optimized vector database (like Pinecone) for near-instant knowledge retrieval. Cross-Platform Parity: I’ll build a central Node.js Middleware API that serves both your JavaScript web widget and your mobile app (REST/SDK), ensuring a unified "Tone of Voice" across all devices. No-Code Knowledge Base: I’ll set up an easy-to-manage Markdown or Google Sheets sync, so your team can update FAQs in real-time without touching a single line of code. Quick question: Do you already have a preferred "Human-Handoff" platform (like Zendesk, Intercom, or a custom socket), or should I build a dedicated dashboard for your live agents? Best Regards, Waqas Ahmed

@hr157

Hi, I’m a full-stack developer with 10+ years of experience, including building AI-driven support systems and scalable integrations across web and mobile. You need a chatbot that’s not just responsive but accurate, fast, and easy to maintain—I’ll design it with a strong NLP backbone and clean integration layer to meet your KPIs. Recommended stack: LLM + RAG approach (OpenAI / open-source LLM + vector DB like Pinecone/Weaviate) for high accuracy Backend: Node.js / Python (FastAPI) for orchestration Fallback/flows: Dialogflow or custom intent layer for structured queries Frontend: JS widget + REST/SDK for mobile integration What I’ll deliver: AI chatbot trained on your products, policies, and tone Web embed (JS snippet) + mobile-ready API/SDK Knowledge base system (non-technical updates via dashboard or CMS) Smart escalation to human agents with >95% trigger accuracy Analytics dashboard (volume, resolution rate, missed intents) Git repo with full source: flows, training data, and integration code Performance focus: Optimized pipelines to achieve <2s response time Structured + semantic retrieval for 90%+ intent accuracy Timeline: Architecture & data setup: 4–6 days Model + backend development: 2–3 weeks Integration + testing + tuning: 1–2 weeks Why I’m a strong fit: 10+ years in full-stack + AI integrations Experience with chatbot flows, APIs, and real-time systems Focus on measurable outcomes (accuracy, latency, reliability) Let's chat!