AI Blueprint Compliance Platform

@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 Matlab, Python, and similar tools. 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

@Ekarthaan

Hi Ben L., Last week I delivered a very similar rules‑based blueprint checker (PDF/TIFF/CAD in, PDF/CSV out), so I’m confident I can handle this really well. i would like to know the below. - Which codes and jurisdictions should we start with (e.g., IBC 2021, NFPA 70/72, ADA/ISO, local ammendments)? - Must everything run fully offline on Ubuntu with Ollama only, and do you prefer a specific Ollama model (e.g., Llama 3.1) for text tagging? I think we should. - Use a hybrid recognizer: vector PDF/CAD parsing for geometry/dimensions, CV detectors (YOLOv8) for symbols, PaddleOCR for notes, Ollama only for ambiguous text. - Define rules in a YAML DSL that compiles to tested Python rules, versioned per jurisdiction for safe updates. Lets follow a plan like this. 1) I set up a Dockerized Ubuntu stack: pdfplumber/ezdxf, PaddleOCR, YOLOv8, rule engine, and Ollama glue. 2) I ingest your three sample sets, train/tune symbol models, and lock scaling to real‑world units. 3) I implement your chosen codes, generate overlays that highlight non‑compliance with sheet/coordinates, and export PDF + CSV. 4) I run accuracy tests, iterate to exceed 80% violation catch, and deliver README + local install scripts. May I know if you are the project owner or part of the direct client team? I usually work directly with the customer, not via agents. Thanks for understanding.

@Microlent

Hi, this is a very strong AI + document-intelligence system especially because blueprint interpretation requires combining OCR, computer vision, spatial reasoning, and configurable rule-evaluation workflows in a scalable architecture. The real challenge is making the compliance engine extensible rather than hardcoding isolated checks. I’ve worked on AI automation systems, OCR/document-processing pipelines, workflow engines, analytics platforms, and rule-driven backend architectures involving structured extraction, reporting, and scalable processing systems. Relevant work: • MetaFlow – AI workflow automation platform • AI extraction/document-processing systems • Real-time dashboard & analytics platforms • More portfolio & case studies: https://www.freelancer.com/u/microlent Approach: • Build a modular pipeline for blueprint ingestion, OCR/symbol extraction, spatial parsing, and rule-engine evaluation • Implement configurable compliance-rule architecture supporting local/national/international code sets and future extensibility Suggested stack: • Python + OpenCV + OCR (PaddleOCR/Tesseract/Azure fallback optional) • Layout/symbol parsing + CV models • Rule engine + vector/spatial analysis workflows I’d strongly recommend beginning with a focused prototype milestone using your sample blueprint set to benchmark extraction accuracy, symbol detection quality, and compliance-rule precision before scaling the full engine. ~ Rajesh

@n2rtechnologies

Hi there, I reviewed your requirements and this looks like something we can handle well. Building an AI system that processes architectural drawings through OCR and ML to flag compliance issues is exactly our wheelhouse — we've done similar document intelligence work before. A couple quick questions: Are you looking to start with a specific drawing format (PDF, image files?), and do you have compliance rule sets already defined, or should we build a configurable framework? I have delivered 1500+ web and mobile projects over 14+ years — happy to share relevant examples. Let's chat through the details. Thanks, Hasan

@koolvishruth

Drawing from my 8+ years of experience and ingrained skills in AI blueprint compliance development, I am well-suited for this project. I have honed my expertise in constructing end-to-end solutions that not only meet client's requirements but also are scalable and user-friendly. Drawing from my proficiency in Artificial Intelligence (AI) & Machine Learning (ML), NLP, Computer Vision, Predictive Analytics, Python Development & Automation, Full Stack Development, Cloud & DevOps among others, your project would be entrusted to capable hands. Let’s connect

@ZohaibRoy

⭐⭐⭐⭐⭐ Create a Code Compliance System for Architectural Drawings ❇️ Hi My Friend, I hope you're doing well. I've reviewed your project requirements and see you're looking for a system to check code compliance for architectural drawings. Look no further; Zohaib is here to help you! My team has successfully completed over 50 similar projects for compliance systems. I will create a user-friendly solution that evaluates drawings against building codes and provides instant reports. ➡️ Why Me? I can easily build your code compliance system as I have 5 years of experience in software development, focusing on OCR, rule engines, and reporting tools. My expertise includes working with multi-page PDFs, CAD files, and implementing effective feedback loops. Additionally, I have a strong grip on technologies like Ubuntu and Olamma AI, ensuring a robust solution. ➡️ Let's have a quick chat to discuss your project in detail and let me show you samples of my previous work. I look forward to discussing this with you in our chat. ➡️ Skills & Experience: ✅ Software Development ✅ OCR Implementation ✅ Rule Engine Design ✅ Reporting Tools ✅ PDF & CAD Handling ✅ Computer Vision ✅ Data Analysis ✅ User Interface Design ✅ Test Automation ✅ System Integration ✅ Feedback Mechanisms ✅ Code Compliance Knowledge Waiting for your response! Best Regards, Zohaib

@codefusion53

Hi, I can build a local, extensible system that ingests drawings, extracts structured data, and runs a configurable rule engine to produce clear compliance reports with visual feedback. I’ve worked on CV + OCR pipelines and rule-based analysis systems where accuracy, traceability, and offline operation matter. My approach is to split this into three robust layers. First, ingestion and recognition: use a combination of OCR (Tesseract or PaddleOCR) and CV models to detect symbols, dimensions, callouts, and text. For CAD exports, I’ll parse vector data where available to improve accuracy over pure image methods. Second, a rules engine: a modular, JSON/YAML-driven system that evaluates constraints like spacing, counts, and code-specific thresholds. This keeps it flexible so you can add accessibility or other checks later without changing core code. Third, reporting and visualization: generate PDF and CSV reports plus an interactive preview that overlays flagged zones with coordinates. The system will run locally on Ubuntu, containerized with Docker, and can optionally leverage local models via Ollama for NLP parsing of notes. I’ll include sample rule sets, test cases, and a clean project structure with documentation for extending rules and retraining components. Best, Justin

@azraazeen9

As a seasoned architect with over a decade of experience in electrical engineering, I understand the need for a precise and efficient platform such as the AI Blueprint Compliance system you're looking for. My extensive expertise in engineering, architectural design, and CAD operations will ensure that the platform can smoothly work with multiple file formats including multi-page PDFs, TIFFs, and CAD exports. Furthermore, due to my knowledge of different software like ArchiCAD, Tekla, Rhino, Abaqus and more I can integrate your desired technology expectations such as running on Ubuntu and Olamma AI into the project with ease. My fluency with AI projects, 2D and 3D modelling will work to enhance the engine's recognition layer. This means it can accurately read symbols, call-outs, dimensions, and notes through OCR and computer-vision routines. Crucially too given my strong understanding of local building codes and international regulations; I can configure your rule engine to comprehensively evaluate each sheet against these guidelines. Not only will this help generate an easy-to-read summary reports but also inform detailed line-item logs for non-compliant entries.

@extreamcode

Hi there, I'm Asad, and I can read the room: you need a robust, self-contained AI blueprint compliance platform that runs locally, ingests multi-page PDFs, TIFFs, and CAD exports, and delivers a trustworthy, rules-driven report with future-proof hooks for accessibility, device counts, and spatial analytics. I’ve built end-to-end ML-powered document and CAD pipelines for compliance and safety checks, and I’ll tailor a modular engine that separates intake, recognition, rule evaluation, and reporting so you can bolt on new checks without rewriting core logic. What you’ll get: a clean, well-structured source tree, a configurable rule-set (local, national, international codes), and a Dockerized/local install path (no cloud deps). The UI/UX will highlight non-compliant zones on the drawing, export PDFs and CSVs, and expose a clear, auditable log of sheet/coordinate-level results. I’ll provide an installation script, a README with retraining steps, and a lightweight preview layer so reviewers can inspect issues fast. I’ve shared an initial estimate based on your description, and once we go over a few technical details, I’ll confirm the exact cost and delivery schedule. What is your preferred baseline set of codes for the initial rule engine (e.g., IBC/ACI/UNI, etc.), and do you already have sample blueprints with embedded violations to validate the 80% target? Best regards, Asad

@quan9824

Hi. I’ll build a rule‑based engine that scans PDF/TIFF/CAD files and flags code violations instantly. Tech stack: Python (OpenCV, PaddleOCR), PostgreSQL, FastAPI, Docker. Runs on Ubuntu + Olamma AI. Core workflow: - OCR + computer vision → extract symbols, dimensions, notes. - Configurable rule engine (JSON/YAML) – local/national/international codes. - Visual violation highlighting on drawing preview. - Export reports: PDF + CSV with sheet/coordinate references. Acceptance: 80% violation detection on 3 sample blueprints. Deliverables: Source code, rule set (sample codes), Dockerfile, README (setup + adding rules). Ready to discuss your first rule set. Doan

@corpmember29

AI-POWERED BLUEPRINT CODE-COMPLIANCE ENGINE FOR AEC DRAWINGS With 12+ years of experience in AI, computer vision, OCR, automation, and enterprise software, we can build a fully local, Ubuntu-compatible compliance analysis system capable of processing architectural, engineering, and electrical drawings with scalable rule-based intelligence. Proposed Solution Includes: • Browser-based or desktop-compatible interface • PDF, TIFF & CAD drawing ingestion pipeline • OCR + Computer Vision for symbols, dimensions, annotations & callouts • Configurable rule engine for local, national & international building codes • Interactive drawing viewer with highlighted violation zones & coordinates • Detailed compliance reports with pass/fail references • Export support for PDF & CSV reports • Modular architecture ready for future: – Accessibility checks – Device/equipment counts – Spatial analytics – Smart-building insights – AI-assisted recommendations Ready to start immediately with architecture planning, OCR pipeline setup, and compliance engine prototyping.

@nickyjohnl

Hello, I have strong experience building document intelligence systems using Python, combining OCR, computer vision, and rule-based engines for technical drawing analysis, including CAD/PDF parsing and structured compliance reporting. I’ve developed pipelines with Tesseract, OpenCV, and layout-aware models, alongside configurable rule engines and local deployments on Ubuntu with containerized setups. To deliver your system, I will design a modular pipeline with file ingestion, OCR/CV-based recognition, and a configurable rule engine that evaluates drawings against defined codes and outputs structured compliance reports with visual annotations. The solution will run locally with Docker, support extensible rule sets, and include reporting in PDF/CSV along with a feedback layer highlighting non-compliant areas directly on drawings. Best regards

@sknadeem123

Hello Client, I hope you are doing well. I came across your project **AI Blueprint Compliance Platform**, and it immediately caught my interest. Based on your description, I’m confident that I can deliver high-quality results that align perfectly with your expectations. **Why I’m a great fit for this project:** • I have strong experience working with Data Processing, Engineering, Software Development, Electrical Engineering, Data Analysis, Machine Learning (ML), OCR, Data Visualization, Computer Vision, Architecture, and I’ve completed similar projects in the past.   • I always focus on clean, optimized, and fully functional work.   • Communication and responsiveness are my top priorities — you’ll always be updated on progress. **What I will deliver:** • A complete and professional solution tailored to your project requirements   • Timely delivery within your budget range of **250.00 - 750.00 USD**   • Clean, well-structured work with revisions included   • A focus on quality, clarity, and long-term reliability If you would like to discuss your project further, I’m available at any time.   I would love the opportunity to work with you and help bring your idea to life. Thank you for considering my proposal. I look forward to working with you! Best regards,   Nadeem Shaikh

@revival786

Greetings, I understand you need a code compliance system for architectural, engineering, and electrical drawings. Input: PDF, TIFF, CAD. Recognition: OCR and computer vision to read symbols, call-outs, dimensions. Rule engine: check against configurable building codes. Output: summary report with line-item log and highlighted redlines. Must run on Ubuntu with Olama AI. Deliverables: source code, configurable rule set, Dockerfile, README. Here is how I will work: I will build a Python-based system using OpenCV for symbol detection and Tesseract for OCR. For code rule parsing, I will allow you to define rules in a JSON or YAML format (e.g., "stair width > 1.2m", "door swing clear".) I will integrate a local LLM via Olama to assist in interpreting complex code clauses and generating readable violation explanations. The frontend will be a simple Streamlit or Flask app to upload files, preview drawings with overlays, and export PDF/CSV reports. I will provide a Dockerfile for easy Ubuntu deployment. I am ready to begin as soon as you share sample blueprints and a list of your highest-priority code rules. Thanks, Revival

@juanjosec63

Hi, I have gone through your project description and understand you want a system that can analyze architectural and engineering drawings and generate automated code compliance reports using OCR + computer vision + rule-based logic. I can build this as a modular pipeline on Ubuntu using Python, combining OCR (like Tesseract or PaddleOCR), CV models for symbol detection, and a flexible rules engine where you can define compliance checks per code standard. The system will process PDFs/TIFF/CAD exports, extract elements, and map them back to coordinates for visual highlighting. The output will include: • Non-compliance reports (PDF + CSV) • Sheet-level annotations with highlighted violations • Configurable rule sets for different standards • Dockerized setup so you can run it locally without cloud dependency I’ll design it so you can later extend it with accessibility checks, spatial analytics, or additional AI layers without rewriting the core. Let’s structure the first version as a working MVP with your sample blueprints ?

@sf264

Hello, I will develop a system that will let you drop a set of architectural, engineering, or electrical drawings into a browser and get an instant, rules based code compliance report. It will run on both Ubuntu and Olamma AI. I would be happy to share my portfolio of similar projects via chat. Let's connect and get this moving forward. Thank you, Fahad.

@solutionsplayers

As a seasoned Full Stack Developer with a primary focus on PHP, Laravel, React JS and Flutter, I have the technical skills and experience necessary to tackle your AI Blueprint Compliance Platform project head-on. For over six years, I have been consistently providing robust, high-performance and scalable applications – the foundational skillsets for your initiative. My knowledge,content proficiency in developing clean, well-documented code has led me to build engaging frontends using technologies like React JS that would become central to running a fluid UI for your platform. Furthermore, my recent journey into the machine learning space with particular emphasis on TensorFlow (also known as Olamma AI) equips me perfectly to handle OCR and computer vision tasks crucial to your Recognition Layer. Your project plans an incredible efficiency boost in blueprints analysis. Entrusting this project with me translates into full-cycle management from ideation through deployment with a client-focused mindset that emphasizes detail. Additionally, by choosing me, my services extend beyond the delivery. You will gain a reliable post-launch support and maintenance partner who is dedicated to your success. Let’s connect today and revolutionize blueprint compliance together!

@SmartCodeDev

Hello, I can build a local first system that processes drawings and generates rules based code compliance reports with a scalable architecture for future analysis modules. I will design a pipeline that handles PDF TIFF and CAD inputs applies OCR and computer vision to extract symbols text and dimensions and structures the data for evaluation. The rule engine will be configurable so you can define local national and international codes with clear pass fail logic and traceable outputs. Reports will include a high level summary detailed line items with sheet and coordinate references and visual overlays highlighting non compliant areas. My key strength here is building modular AI driven systems that combine document understanding with rule based validation in a production ready workflow. The solution will run on Ubuntu with local models compatible with Olamma and include a Docker setup for easy deployment without cloud dependency. You will receive clean source code sample rule sets export to PDF and CSV and a clear README for setup retraining and extending rules. I can start by reviewing your sample drawings and defining the first rule set to meet the accuracy target. Let me know your timeline and sample files so we can proceed.

@shadabkhan92

I already build similar tasks based on image blueprint the system recognize patterns and provide compliance along with other. lets discuss