Door Ironmongery AI Estimator APP

@infowider11

⭐️⭐️⭐️ Proposal: AI-Powered Floor Plan Door Detection & Recommendation Platform⭐️⭐️ We will build a fully browser-based AI application that processes uploaded floor plan PDFs, detects and counts doors using computer vision models, and intelligently maps them to your product catalogue for accurate recommendations. The system will include a scalable backend with a trained ML pipeline capable of handling varied architectural layouts and continuously improving through your supplied data. The frontend will feature a clean, intuitive interface where users can upload plans and instantly receive analyzed results, including door counts and matched product suggestions based on specifications. An advanced admin panel will allow you to manage your catalogue, update product data, and retrain or fine-tune the AI models without technical complexity. Our approach will leverage modern technologies such as React for the UI and a php/Node-based AI service for PDF parsing, model inference, and recommendation logic, ensuring modularity and future scalability. The solution will be fully web-based, deployed on a cloud platform, and optimized for performance and accuracy. Deliverables will include a live deployed application, trained AI model with a documented inference pipeline, admin dashboard, and complete source code with setup documentation. Let’s chat…! Thanks

@irsolutions

With over a decade of experience in full-stack architecture and high-scale systems, I understand the need for a browser-based AI app tailored specifically to door ironmongery estimation. Your project goal of automating floor-plan parsing, door count analysis, and recommending suitable door models aligns perfectly with my background in high-complexity systems. My past success in building and scaling Telegram Mini Apps serving over 1 million users showcases my ability to handle projects of this level of complexity. To ensure the scalability and security of your Door Ironmongery AI Estimator App, I recommend implementing a robust training data pipeline alongside regular model retraining. This strategy will not only enhance the accuracy of door counts but also ensure that the recommendation engine remains up-to-date with your evolving product range. I invite you to reach out to discuss how we can collaborate on this project. I am confident that my expertise in AI, web development, and database management can help bring your vision to reality. Let's connect and chart out a roadmap for creating a cutting-edge solution for your door ironmongery estimation needs.

@kamran2012

I can help with this, I will build the browser-based door ironmongery estimator — PDF floor-plan parsing, automatic door detection and counting, and a recommendation engine that maps each detected door to your catalogue. For the vision pipeline, I will convert each PDF page to high-resolution images, then run a fine-tuned object detection model to locate and classify door symbols by type — single, double, sliding, fire-rated. Each detection feeds into the recommendation engine, which scores your catalogue items against the door type and the client's stated specs. This two-stage approach keeps detection accuracy separate from product logic, so you can retrain either piece independently from the admin panel without disrupting the other. Looking forward to potentially working together. Thanks, Kamran

@Walkingdreams

With over a decade of experience in handling complex projects like yours, my team at Walking Dreamz Technologies is poised to deliver you a streamlined, user-friendly, and high-functioning browser-based AI app that will certainly meet your requirements of counting doors and suggesting the perfect models for your clients. Our specialized skills are similar to your project's needs. We have a vast experience in MERN stack development which would help us in building your web app with the AI vision and machine learning algorithms performing effortlessly in the backend. My team is also well-versed in utilizing AI for automation purposes, which can be seen through our previous works involving chatbots and workflow automations, all resulting in positive reviews from online business owner - just like you. As we value clear communication, clean code and predictable delivery, you can expect a transparent working relationship with timely milestones, frequent demonstrations, and transparent progress updates from us. We'll ensure that the final product not only delivers on the stated objectives but also provides an intuitive interface for both the end-users and the admin area where you can update the product database and retrain models as needed. The scale of our previous projects has given us fine-tuned management abilities to handle all types of data more efficiently.

@aadips

Hi, I've reviewed your Door Ironmongery AI Estimator project and I'm excited about building this for you. At Webneco Infotech, we specialize in AI-powered web applications and have hands-on experience with computer vision, PDF parsing, and machine learning pipelines. My approach: I'll build a browser-based app where users upload a floor plan PDF, our AI vision layer detects and counts every door opening, then maps each door type to your product catalogue using a trained recommendation engine. The admin panel will let you update the catalogue and retrain models without developer help. Tech stack: Python/FastAPI backend with OpenCV + a fine-tuned object detection model (YOLO or similar), React frontend, PostgreSQL for the product database, and Docker deployment on your test server. A few quick questions to scope this accurately: 1. Do you have existing annotated floor plan data for training, or do we start fresh? 2. How large is the door catalogue (number of SKUs)? I'd love to discuss the technical architecture in more detail. Let's connect!

@techsty2014

Hi there, I will build the app with a Python backend: PDF rasterization, vision-model door detection per page, structured output of count, type (single, double, sliding, fire), and dimensions where extractable, plus a rule-based recommender filtering your catalogue by type, width, and stated specs. Admin panel for catalogue maintenance ships with the source. The call at this budget: use a frontier vision model (Claude Sonnet, GPT-4o) on rasterized pages rather than training custom YOLO. Custom symbol detection needs thousands of labeled floor plans and would burn the budget on labeling alone. Frontier vision handles door symbols across drafting standards, with calibration on your typical PDFs to validate accuracy. Questions: 1) Catalogue size and spec fields driving matching (width, fire rating, hardware)? 2) Drafting standard (AIA, ISO, BS, mixed)? 3) Sample PDFs for calibration? Looking forward to talking through the details. Best regards, Faizan

@tushortz

Hello, I understand you need a web-based AI app to analyze architectural floor plans, count doors, and recommend suitable door ironmongery products from your catalogue. This aligns well with my expertise in backend development, AI integration, and UI/UX design. I'm Taiwo, a UK-based Senior Software Developer with 10 years of experience and a Master’s in Cyber Security. I've built scalable backend systems for companies like IBM, UK Government, BMW, and Sky, therefore building secure, reliable, and user-friendly platforms is something I am well versed in. My approach involves: ⏺ Analyzing floor plans for door identification and quantification using AI models, ⏺ Developing a recommendation engine that integrates with your product catalogue ⏺ Creating an intuitive web app using Django framework along with an admin panel for database and model management. ⏺ Finally, deploying to a test server to give you a chance to test it. Relevant projects: ⏺ OneKey platform and Equity Share showcase my ability to develop scalable web-based applications with complex backend logic. ⏺ GitSecure demonstrates my commitment to secure coding practices. If this approach aligns with your vision, I can start immediately.

@markupdudes

Hi, I’ve carefully reviewed your requirements for the Door Ironmongery AI Estimator App, and I'm confident I can deliver a robust, browser-based solution tailored precisely to your needs. With extensive experience in AI development, computer vision, and web app architecture, I will build an intuitive interface that reads floor plan PDFs, accurately detects and counts doors, and matches each door to your supplied product catalogue through a smart recommendation engine. I understand the importance of seamless model training and updates, so I will also develop a comprehensive admin panel for you to maintain and retrain the product database effortlessly. The app will be fully web-based with no native installs and will come deployed on a test server with complete source documentation. Let’s start with deploying an initial prototype for door detection and recommendation within 21 days, then iterate based on your feedback to perfect accuracy and usability. Could you share some example floor plan PDFs and initial product data to help tailor the training process? Best regards,

@mobasherreza10

Hi there, I see you need a browser based AI app that takes a floor plan PDF, automatically reads the drawing, identifies every door, counts them, then recommends specific door models from your catalogue based on client specifications. I recently built a similar system for a window manufacturer where users uploaded floor plans, the AI vision model detected all window openings and sizes, matched them to a product catalogue, and returned a bill of materials with estimated pricing. The system used a fine tuned YOLOv8 for object detection on PDF converted images, plus a rule based recommendation engine that mapped detected door types and dimensions to catalogue specifications. Accuracy was 94% on test floor plans. I would love to do the same for your doors. My approach is to use a vision model (YOLOv8 or a custom trained Faster RCNN) to detect door symbols and openings from PDF converted images, extract door type (single, double, sliding, etc.) and approximate dimensions, then feed those features into a recommendation engine that queries your product catalogue for matches based on type, size range, material, and client specifications you capture in the UI. The admin panel will allow you to update the product database and retrain models. I will deploy to a test server and provide source code with setup documentation. Best regards, Mobasher Reza

@jay8mac

Lets chat, a free consultation and no obligation. I understand you need a clean, professional, and user-friendly solution for your "Door Ironmongery AI Estimator APP" project. My skills in PHP, Java, JavaScript are a perfect fit for this project. While I am new to freelancer.com, my extensive experience delivers integrated, automated solutions. Regards, Jason McLachlan

@vertechsolutions

Hi, I can fix your Door Ironmongery AI Estimator APP I've solved this exact problem many times. Here is what I will do: • Build a browser-based PDF workflow to upload floor plans, extract door symbols, and count openings accurately. • Develop the AI vision and recommendation engine to map detected door types to your supplied catalogue and spec sheets. • Create a clean admin panel to manage products, update data, retrain models, and deploy everything to a test server. 10 days free support after delivery Milestone-based payment Reply "YES" and Best regards, syed ribal