Commercial Property Finder Chatbot

@PINESCRIPTERR

Hi, I’ve built Google Assistant agents with Actions Builder/Dialogflow and can share examples directly in chat. I will deliver: 1. Dialog model with core intents (location, budget, square footage, subtype) and natural slot‑filling that probes for missing details 2. Fulfillment service (Node.js or Python) deployed on GCP, returning structured results with rich responses (cards/carousels) where supported 3. Data integration to a sample or live commercial‑property API with graceful fallback messaging and mock dataset for testing 4. Voice and text surface tuning so flows feel natural on Google Assistant, including confirmation prompts and quick replies 5. Clean, well‑documented code ready for hand‑off, plus a brief setup guide and video walkthrough using the Assistant simulator Please feel free to reach out so we can discuss timeline and price. Best regards, Houssame

@forsovateam

Our team at Forsova is excited to build your Google Agent for commercial property discovery, ensuring seamless conversational flows on both voice and text for Google Assistant. We will deliver a robust dialog model, clean fulfillment code in your preferred language, integration with a mock or live data feed, and rich responses like cards or carousels as device-appropriate. Comprehensive setup documentation and a clear video walkthrough will ensure a smooth hand-off and easy deployment in your GCP environment.

@malkesh3m

⭐ Hello there, My availability is immediate. I read your project post on Python Developer for Commercial Property Finder Chatbot. We are experienced full-stack Python developers with skill sets in: Python, Django, Flask, FastAPI, Jupyter Notebook, Selenium, Data Visualization, ETL AI/ML & Data Science: Model development, training & deployment, NLP, Computer Vision, Predictive Analytics, Deep Learning React, JavaScript, jQuery, TypeScript, NextJS, React Native NodeJS, ExpressJS Web App Development, Web/API Scraping API Development, Authentication, Authorization SQLAlchemy, PostgresDB, MySQL, SQLite, SQLServer, Datasets Web hosting, Docker, Azure, AWS, GCP, Digital Ocean, GoDaddy, Web Hosting Python Libraries: NumPy, pandas, scikit-learn, TensorFlow, PyTorch, etc. Please send a message so we can quickly discuss your project and proceed further. I am looking forward to hearing from you. Thanks

@chiragardeshna

Hi there, I have expertise in conversational AI, Google Assistant agents, PM, QA, and deployment. I reviewed your project. You need a Google Assistant property finder agent for commercial listings, handling voice and text, probing for missing details, querying a mock or live dataset, and returning structured results (cards or carousels). Node.js or Python fulfillment, clean code, and fast turnaround are required. I deliver dialog models, fulfillment code in your GCP project, API or mock data integration with fallback handling, and a setup guide with simulator walkthrough. Regards Chirag

@providenceoghal3

Commercial searches fail when the questions aren’t smart. Users want answers, not filters. This agent delivers both, naturally. I like how clearly you’ve defined the goal: a conversational, Assistant-native property finder that understands commercial intent and guides users to the right listings without friction. That’s exactly how I’d approach this, building an agent that asks intelligent follow-ups when details are missing, interprets constraints like location, size, budget, and property type, and returns clean, structured results that feel right on both voice and text surfaces. I’d implement the agent using the official Google Assistant development kit and Actions Builder, with a well-scoped dialog model, robust intent handling, and fulfillment logic in Node.js or Python inside your GCP project. Results would be formatted dynamically, using rich responses (cards/carousels) where supported, and graceful conversational summaries where not. The data layer would connect to your feed or a mock commercial dataset first, with clear seams for swapping in live data late, no rewrites required. The code will be clean, documented, and easy to extend, with a setup guide and short walkthrough video so your team can test, iterate, and integrate confidently within your one-month timeline. Out of curiosity, will the first live data source be a single listings feed, or multiple brokers aggregated behind one API? Message me now so that we can begin.

@Lerikus

Our background makes us well-suited to handle this project effectively, I’ve successfully delivered work comparable to what you need. Your requirement for a conversational Google Agent focused on commercial property listings, with seamless integration, user-friendly probing for missing details, and delivering clean, professional, and structured responses aligns perfectly with our expertise. We offer extensive experience in developing conversational agents using Google Assistant SDK and Actions Builder. Our skills in Node.js and Python ensure clean, well-documented, and automated fulfillment code. While our company is new to the freelancer platform we are not new to the industry, we have a wide range of experience and expertise connecting APIs and delivering elegant, integrated solutions quickly and reliably. I’m available to discuss the project in more detail whenever you are ready. Regards, Lerikus

@dhruvenb7

I will build a Google Assistant conversational agent using the official SDK that helps users find commercial properties through natural voice or text interactions. The agent will intelligently gather missing details such as location, budget, square footage, and property type, then return matching listings in a clear, structured format using cards or carousels when supported. I’ll deliver clean, well-documented Node.js or Python code deployed on GCP, integrated with a sample or live commercial property API, along with a setup guide and a short walkthrough video to ensure easy hand-off and future real-data integration.

@dhananjaym23

Hi, I’ve worked on backend systems and conversational workflows where the core challenge is understanding user intent, filling in missing context, and reliably mapping natural language requests to structured data queries. For this project, I can build a Google Assistant agent using the official SDK that handles both voice and text interactions smoothly. The agent will guide users through location, budget, size, and property type, ask follow-up questions when needed, and return clean, structured results using cards or carousels where the surface supports it. I’m comfortable starting with a mock or sample dataset and designing the fulfillment layer so it can be swapped to a live commercial-property API later with minimal changes. On the implementation side, I can deliver well-documented fulfillment code (Node.js or Python, based on your preference), deploy it cleanly on GCP, and provide a short setup guide plus a walkthrough video showing the agent running in the Google Assistant simulator. I prefer keeping the first phase focused on a solid conversational flow and clean architecture, so future enhancements and real-data integration remain straightforward. Happy to start with a quick discussion and align on the data source and response format before implementation. Regards, Dhananjay

@mohamedelamra

Hello, I can build a Google Assistant conversational property finder using the official Google Assistant SDK / Actions Builder, focused specifically on commercial listings and optimized for both voice and text surfaces. How I’ll implement it • Intent-driven dialog model covering location, budget, size, and property type • Smart follow-up questions to collect missing details naturally • Fulfillment in Node.js or Python, fully runnable in your GCP project • Integration with a mock or live commercial property API, with graceful fallback messaging • Rich responses (cards / carousels) where the device supports them Quality & Handover • Clean, modular, and well-documented code • Tested in the Google Assistant Simulator • Setup guide + short video walkthrough for easy handoff and future data integration Timeline & Rate • Ready for deployment within 3–4 weeks • Hourly rate: ₹230 INR/hour (up to 40 hrs/week) I have experience building production-ready conversational AI, handling intent resolution, structured responses, and API-driven fulfillment on GCP. I focus on clarity, maintainability, and smooth user experience. Happy to discuss your data feed and deployment preferences. Best regards, Mohamed