Comprehensive AI Real Estate Sales System

@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 Python, and similar tools. I have worked with pytorch, and tensorflow to develop DL models, .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

@Hrolgar

Before any code there's a choice to settle: let the model decide what to show buyers, or let it only do the talking while the database decides what's on offer. Free-form search feels more human on WhatsApp, but one 2BHK in Andheri sent to someone who asked for a 3BHK in Powai and the broker stops trusting the whole thing. I'd go with the second. The agent calls a search tool with budget, BHK and locality as hard filters, and it can only recommend what comes back. Qualification runs as a proper state per lead (budget, location, BHK, timeline, then ready or not), so the follow-ups and the broker alert fire off that state rather than off how the chat feels. Site visits get booked against slots the broker sets, and the dashboard shows leads, stages and visits. 60,000 INR is a starting figure off the brief. I'll firm it up once I've seen how clean the inventory data is and whether you're on the official WhatsApp Business API. M1: inventory database, hard-filter search, WhatsApp webhook wired up, 19,800 INR, 4 days. M2: qualification flow, recommendations, site visit booking, 20,000 INR, 4 days. M3: automated follow-ups, broker alerts, dashboard, 20,200 INR, 4 days.

@SahilRao1247

Having been an AI Content Creator for over 9 years, I believe I have the unique set of skills needed to bring your comprehensive AI Real Estate Sales System to life. I have extensive experience in content creation, video editing and production, 3D design and animation as well as music and sound production which all aligns seamlessly with your project requirements. My exposure within various industries including advertising, entertainment, architecture and gaming has given me an intuitive understanding of how best to make AI work for your real estate project. The use of LLM such as OpenAI is something that I am familiar with. I also understand the value of API integrations, creation of WhatsApp bots as well as incorporating RAG/ vector search which should be advantageous for your project. Furthermore, with my experience in full-stack development, I am not only knowledgeable about constructing the technical aspects but also about understanding user needs.

@saba106

I am an expert statistician, Research Writer, and data analyst with more than eight years of experience. I have full command of Excel analysis, SPSS, STATA, R LANGUAGE, AND PYTHON. I am an expert in creating time series prediction models, working with survey data, conducting marketing analysis, building estimators, and medical analysis. I am a perfect match for your project share other details of the work so I can start working on your project. Will complete task on time.

@UzeeTech

Mumbai property buyers message several brokers at once and go with whoever replies first, so an AI agent that answers instantly on WhatsApp can genuinely change how many site visits your clients book. I would build this with a large language model connected to the WhatsApp Business API and a property database, so the agent answers questions on price, location and availability from real inventory and hands over to a human broker only when the lead is warm. I would add a simple CRM view where brokers see every conversation, lead status and follow up reminders, plus broadcast templates for new listings. The bot would be trained on your past chats so its tone matches how your team already speaks to buyers. I would also set up quick reply templates for common questions so the bot stays fast and consistent. I built Jyotish AI, a live AI app on Android and web, so I work with language models and production AI features every day. Two questions: where does your property data live today, in spreadsheets or an existing system, and should the agent reply in English, Hindi or both? If we confirm these details I can share a precise timeline and get started.

@jaroslavcaprata

Hi, Thanks for sharing the details of your AI real estate sales system. This project is a great match for my experience building AI-powered applications, LLM workflows, chatbot systems, and full-stack platforms. I have experience designing AI solutions that combine LLMs, API integrations, structured data, automation workflows, and backend systems. For your MVP, I can help architect the AI sales agent workflow, integrate WhatsApp communication, connect property inventory with intelligent search, and build a reliable system that can qualify leads, recommend properties, and hand over conversations to brokers when needed. I understand that the goal is not just creating a chatbot, but building a practical AI assistant that improves real-world sales conversion. I would focus on creating a simple but scalable foundation with proper conversation handling, data retrieval, lead tracking, and future expansion possibilities. I’m interested in understanding more about your current property data source and workflow. Do you already have a structured property database/CRM, or would the MVP need to include the initial inventory management system as well? I’d be happy to discuss your vision and help turn this idea into a working product. Best regards, Jaroslav Caprata

@Cruz1217

Hi, handling multiple enquiries from potential buyers on WhatsApp is where things can get tricky, I'd approach this by setting up a real-time sync between the WhatsApp Business API and the property database to ensure the AI sales agent has access to the most up-to-date property inventory. This way, the AI can quickly recommend relevant properties to buyers based on their budget, location, and other preferences. I'll set up the AI workflow to automatically follow up with interested leads and notify the broker when a lead is qualified. In my experience, one common mistake is not properly testing the AI agent with real-world conversations, which can lead to unexpected errors and poor performance, I'd start by building a simple dashboard for the broker to track leads and site visits, and then focus on integrating the LLM and WhatsApp Business API to create a seamless conversation flow. The client can expect a working MVP that can handle enquiries, recommend properties, and arrange site visits, with the potential for further expansion based on market feedback.

@paruls154

Hi With a decade of experience as a developer, I am well-versed in building end-to-end solutions that align with real business needs – not just checking boxes. My expertise in AI Chatbot and AI Chatbot Development, coupled with my ability to integrate applications and APIs, fits seamlessly with your vision for this project. Think of me as an integral part of your team dedicated to the project's success long after its inception. Let's connect and discuss how I can add value. Regards Parul Saini

@TechWagger2026

As the founder and lead developer of TechWagger, I feel confident in my ability to deliver the comprehensive AI-based real estate sales system you require. Our company is well-versed in tapping into the power of artificial intelligence for a range of applications, including chatbot development, API handling, and database management. Together, this unique set of skills means we can take your vision from an idea and translate it into a tangible, functional MVP that prioritizes relevant recommendations and efficient lead nurturing. One key aspect that sets me apart is my emphasis on practicality and user-focus. While many developers tend to over-engineer solutions, at TechWagger we believe in building for real-world needs. We understand that you want to test this AI solution with real Mumbai brokers and are committed to delivering a product that aligns with your vision while staying nimble enough to adjust based on market requirements. Lastly, my team's track record speaks to our ability to deliver scalable solutions that stand the test of time - something critical for your project as it grows from an MVP developed on WhatsApp API into a full-fledged system integrated with CRM. It would be an honor to collaborate with you not just for this development project but potentially as your technical partner long term as you embark onboarding clients. Let's embark on this journey together; I'm excited to make your brilliant concept a powerful reality.

@FreeLancers360

Hi there, The moment I read "Comprehensive AI Real Estate Sales System", I knew it was a strong match for exactly what we do best. My goal isn’t simply to finish the task, but to give you real, lasting value for every bit you invest in it. From your brief I can see this involves ai, machine learning, llm — all areas we handle in-house. We specialise in Machine Learning (ML), API Development, AI Chatbot Development, AI Chatbot, which lines up directly with what you need. How we'd approach it: - Clarify the use-case, inputs and the exact output you expect - Build and integrate the model / automation pipeline - Evaluate accuracy and tune against real examples - Deploy with monitoring and a clear handover I’ll fold in your feedback fast and keep refining until the result feels exactly right to you. I can start right away and keep you updated at every step — let’s make this a great one. Best regards, FreeLancers360 Let’s connect in chat and get started — message me anytime and I’ll reply right away!

@michela542

Hi, ➤ The hardest part of a system like this is the property matching. The AI has to correctly pull out what the buyer actually wants (budget, location, BHK, timeline) from a normal WhatsApp conversation, then search real inventory and recommend properties that genuinely fit, without missing the buyer's intent or suggesting something off-target that kills trust in the "salesperson" right away. ✅ I ran into this exact challenge on a similar AI agent project. The main issue was getting the AI to reliably extract structured buyer criteria from loose, natural conversation and match it against real inventory instead of just keyword-matching. I solved it by using the LLM to extract structured fields (budget, location, BHK, purpose) turn by turn into a conversation state, running that against the property database with a vector search layer for flexible matching on things like location and description, and adding a simple confidence check before a property got recommended, so the AI only proposed listings it was actually confident fit. ✅ That approach worked well. The AI consistently picked out the right buyer criteria across varied conversation styles, property recommendations matched what buyers actually asked for, and qualified leads got flagged to the broker accurately without flooding them with unqualified enquiries. With only this kind of experience, I can help you, looking forward to discussing with you about your vision. Best regards, Michel.

@obademio1

Hi, hope you are well. I have read the details you shared and I understand the outcome you want. I am a skilled freelancer with 10+ years of experience in API Development, AI Chatbot Development, AI Content Creation, AI Development and I have completed similar projects. Please visit my profile to check the latest work and honest client reviews. I would love to connect in chat to discuss details. Best regards, Olusoji

@Visharaa2024

Hi, The key to this MVP is making the AI behave like a junior salesperson, not a generic chatbot. I’d keep the broker’s property inventory as the source of truth and separate AI conversation/qualification from deterministic property search and availability. I’d build the MVP with Node.js/Express and PostgreSQL, integrate the WhatsApp Business API and an LLM such as OpenAI, and create structured workflows for requirement extraction, property matching, lead capture, site-visit requests, follow-ups and human handoff. The broker dashboard can initially stay lightweight, focused on leads, conversations, requirements, recommendations and visits. For V1, I’d start with structured PostgreSQL filtering for budget, location, BHK, purpose and availability rather than over-engineering a vector system. AI can then explain and present verified matches naturally. One key question: will the broker provide property inventory through a CSV/admin interface, an existing CRM/API, or another source? If this aligns with your MVP approach, we can proceed with the conversation flow and property-data architecture. Best regards, Deepak.

@danino29

One broker, one number, a small property list, that's the whole first version. The part that decides whether this works is matching buyer criteria against real inventory correctly, not the conversation polish. I'd start by getting that search logic solid, budget, location, BHK, timeline as structured filters over the property data, then add enquiry handling and lead capture once it's returning the right matches every time. I built a similar ops agent for a short-term rental business, handling guest messages and pricing logic end to end. Is the property list already in a spreadsheet or CRM, or does that still need setting up?

@theyasirahmad

I can build this MVP as an AI sales agent focused on actually qualifying Mumbai real-estate leads and converting enquiries into relevant property recommendations and site visits, rather than just answering FAQs. I’d use WhatsApp Business API + OpenAI with a structured property database and backend workflow. The agent will capture budget, location, BHK, purpose, timeline, and preferences, search the broker’s live inventory, recommend matching properties, answer property-specific questions, collect lead details, and trigger site-visit requests. I’ll also build automated follow-ups based on lead status and notify the broker when a lead is qualified, interested, or needs human intervention. For property matching, I’ll combine structured filters with RAG/vector search where useful, while keeping critical property facts grounded in the actual inventory. For the MVP, I’d keep the architecture simple: Node.js/NestJS backend, PostgreSQL, OpenAI, WhatsApp Business API, and a lightweight broker dashboard. The system will include conversation logging, lead management, prompt/config management, error handling, and API-ready architecture for future CRM integrations. I can take this from architecture through development, real-world conversation testing, deployment, and iteration with your first broker. Regards, Yasir

@ektaa15

Dear Client, I would be happy to help build your AI-powered real estate sales system and MVP. I understand that the main goal is to create an AI sales agent that can handle WhatsApp enquiries, understand buyer requirements, recommend suitable properties, qualify leads, and help arrange site visits. I can work with technologies such as OpenAI APIs, WhatsApp Business API, property databases, RAG or vector search, automation workflows, and a suitable full-stack framework. I can design the system so the AI uses the broker’s actual property inventory instead of giving generic responses. For the MVP, I would keep the architecture simple and practical: one broker, one WhatsApp number, and a focused property database. I can build the conversation flow, lead qualification, property matching, follow-ups, broker notifications, and a simple dashboard if required. I will also test the system with real-world conversations and improve the workflow based on results. I am ready to discuss the MVP and start building quickly. Best Regards, Ekta

@aakaashberi

The difference between a generic chatbot and a junior salesperson is that it only recommends flats that really exist in the broker's inventory, and knows when to hand over to a human. That is what I'd build the MVP around. How I'd build it: WhatsApp Cloud API webhook into a Node/Python backend. The LLM extracts budget, location, BHK, purpose and timeline into a lead record, then calls a property search over Postgres (hard filters plus vector search on descriptions), so every answer is grounded in real listings. Site-visit booking, template-based follow-ups within WhatsApp's rules, and an instant broker alert when a lead is qualified or asks for a human. A simple dashboard shows leads, chats and visits. First working version in 4 days, tested on real enquiry scripts. Price: Rs 12,500 fixed for the MVP (one broker, one number, their inventory). Two questions: is the broker's WhatsApp number already on the Business API, and where does the inventory live today (Excel, CRM or a portal)? Aakaash

@abhilashr53

You want to build an AI junior salesperson for Mumbai real estate brokers that turns WhatsApp enquiries into qualified leads and booked site visits, without the broker lifting a finger until the lead is ready to talk. Here is how I would approach the MVP. The core stack would be WhatsApp Business API via Twilio or 360dialog feeding into a Node.js backend, OpenAI GPT-4o handling conversation logic with structured prompts to extract budget, location, BHK, timeline and purpose, a PostgreSQL database for property inventory and lead state, and a simple React dashboard for the broker to view leads, update listings, and get notified when a lead qualifies. Automated follow-up sequences would run via scheduled jobs, with broker alerts sent through WhatsApp itself for instant response. The risks I would handle upfront are conversation context drift across long threads, Hindi-English code-switching which is standard in Mumbai buyer conversations, and WhatsApp API approval timelines, so we start that process on day one. My background spans LLM integration, WhatsApp automation, and full-stack product builds, and I think four to five weeks gets you a working single-broker MVP you can actually demo to investors or early adopters. What does your property inventory look like currently, and do you have a preferred way buyers typically phrase their enquiries?

@aniketb2091

Hi! This project is a great fit for how I like to work — build something functional fast, test it with real users, then iterate based on what actually breaks. I've built and deployed a production AI application using the Gemini API with structured prompt engineering (a live recommendation engine, currently in production), so I'm comfortable working with LLMs for structured extraction tasks like pulling budget/location/BHK/timeline out of natural conversation. I also have solid full-stack experience (React, Node/Express, MySQL/MongoDB, Firebase/Supabase) for the CRM and dashboard side. WhatsApp Business API integration specifically is newer territory for me, so I want to be upfront about that rather than overpromise — but the architecture (webhook handling, API integration, structured data flow) overlaps heavily with work I've already shipped. I'd want to scope in a few extra days of buffer specifically for the WhatsApp setup/approval process, since that part has dependencies outside either of our control (Meta's business verification). Given the full scope — agent logic, property matching against inventory, lead qualification, and a basic broker dashboard — I'd suggest 12–14 days rather than 8, to build this properly rather than rush the AI logic (which is the part that actually needs to work well for this to be useful to a broker). Happy to hop on a call first to walk through your vision in more detail before locking in the plan.