Need to build Agent AI for Quotation Creation

@Mahihassi

As an AI and Cloud Developer, I have had extensive experience in designing and implementing intelligent applications similar to what your project entails. My deep understanding of AI and robust backend architecture design using tools like Python, LangGraph, LLM or even available AI like claud makes me confident that I can build the Agent AI you're seeking. Furthermore, my proficiency with creating APIs and integrating cloud platforms will enable flawless communication between the ERP system and the Agent AI. Throughout my career, I have developed cutting-edge solutions that leverage AI models to automate complex tasks successfully. This includes processes such as data extraction, analysis, and decision making which align perfectly with the key functionalities of the Agent AI you envision. My approach to building intelligent systems revolves around utilizing semantic understanding rather than inventing new information. In addition to the functional requirements of your project, I also place immense importance on scalability and performance optimizing implementation. This ensures that not only will your Agent AI deliver accurate quotes but also handle increased loads as your business expands. Let's discuss your budget and timeline further to determine whether we build an Agent AI completely from scratch or leverage existing AI technology for cost-effective and timely delivery. Let's help unleash the power of AI in revolutionizing your quotation creation process together!

@softwarelinkerrs

"Drawing from my reputable experience in developing robust and scalable digital systems for various industries, I am confident that my team at SoftwareLinkers is well-equipped to successfully execute your project requiring an Agent AI for Quotation Creation. Our proficiency in Python, coupled with an extensive understanding of ERP systems (such as the one built with PHP for this project), will allow us to create an optimal API solution that enables smooth communication and flow of data between the ERP system and the Agent. In addition, our familiarity with implementing AI-powered features into existing systems will save time and resources as we can leverage available AI technologies like LLM, LangGraph, or even popular platforms such as cloud services if it aligns with your cost and timeline requirements. Moreover, our strength in maintaining long-term relations with clients is testament to our commitment in delivering on-time projects with efficient communication. You'll never have to worry about delays or miscommunications when we're working together. Finally, what truly sets us apart is our thoughtful approach. We not only excel at coding but also place heavy emphasis on understanding your business needs, which in turn ensures the solutions we create are not just technologically efficient but are also seamlessly aligned with your specific goals. Let's join forces now and bring an unmatched AI-powered efficiency to your quotation process."

@kamran2012

Good to see this project, I will build your quotation AI agent — intake parsing from email, PDF, images, and web enquiries, semantic product matching against your ERP, automated quote generation with validation, and the approval-to-customer dispatch workflow. For the product mapping, I will use embedding-based semantic search over your ERP catalog rather than keyword matching. This means the agent retrieves the closest real products without hallucinating items that do not exist — paired with a strict constraint layer that blocks any product not found in your ERP. I will architect this with LangGraph for the multi-step orchestration and provide you a clear cost and timeline comparison between a custom LangGraph/Python build versus a Claude-based agentic approach. Looking forward to talking through the details. Kamran

@hr157

Hi, With 10+ years of experience in AI workflows, automation systems, ERP integrations, and full-stack development, I can help architect this properly and safely. Recommended architecture: - Python + FastAPI backend - LangGraph/LangChain orchestration - LLM-assisted extraction + semantic matching - Vector search/embedding layer for product mapping - PHP ERP API integration - Human approval workflow before customer delivery Core flow: Email/PDF/Image/Web enquiry → Data extraction → Semantic requirement analysis → ERP product matching → Quotation generation → Key focus areas: - Strict grounding from ERP data only - No hallucinated products/pricing - Confidence scoring + validation checks - Human-in-the-loop approval workflow - Structured audit/logging Two implementation approaches: 1. Custom AI Agent (LangGraph/LLM/Python) Pros: - Full control - Better workflow customization - Easier ERP-specific logic - Scalable long-term Timeline: 6–12 weeks depending on ERP complexity and document variability 2. Hybrid using Claude/OpenAI APIs Pros: - Faster deployment - Lower initial development cost - Strong extraction/summarization capability Important: The real complexity is: - Semantic product matching - Reliable extraction from messy documents/images - ERP normalization - Preventing hallucinations A few important questions: - How structured is the ERP product catalog? - Do quotation templates already exist? - Are enquiries mostly PDFs/emails or mixed formats?

@techsty2014

Hi there, I will build the agent on Claude with LangGraph orchestration: ingest from email, PDF, image OCR, and website forms, extract structured fields, query your ERP via the new API for matching products, draft and self-check the quotation, then route to sales for approval before customer dispatch. The "must not invent" rule is the architectural pin. I will enforce it with retrieval grounded against your catalog plus a strict output schema: if no product matches above a confidence threshold, the agent returns null and routes to a human. An eval suite of historical quotations runs on every release so regressions surface before customers see them. Questions: 1) ERP database (MySQL, PostgreSQL, other) and roughly how many SKUs? 2) Quotation output: PDF, Excel, or HTML email? 3) Approval workflow: single approver, multi-stage, or role-based? Looking forward to talking through the details. Best regards, Faizan

@mahig47

Hello! As per your project post, you’re looking to build an AI powered quotation generation agent that can automatically process customer enquiries from emails, PDFs, images, and website submissions, map requirements against your existing ERP product database, and generate accurate quotations for sales team approval before sending them to customers. My focus will be on delivering a complete Agent AI system built using Python, LangGraph, LLM workflows, and semantic product matching architecture, including multi source enquiry ingestion, OCR and document parsing for PDFs/images, structured data extraction, ERP API integration with your existing PHP system, semantic product mapping and validation logic, quotation generation workflows, approval routing to sales teams, audit trails, and automated customer communication after approval. I specialize in building AI agents, workflow automation systems, and enterprise AI integrations using Python, LangChain/LangGraph, vector databases, LLM orchestration, OCR pipelines, ERP/API integrations, and scalable backend architectures. My focus will be on creating a production ready AI quotation engine that is reliable, explainable, maintainable, and capable of scaling with your sales operations. Let’s connect to review your ERP structure, product catalog logic, quotation workflow, and preferred AI architecture so we can finalize the implementation roadmap and validation strategy. Best regards, Nikita Gupta.

@ModernTechno442

With over 7 years of solid experience in web design and development, our team at Kajal understands the importance of creating tailored solutions to meet the specific needs of each client. We've successfully built numerous AI-powered systems for various businesses, employing a range of tools including LLM, LangGraph, and Python - the very skills you are looking for. Our expertise extends to integrating existing ERPs with different systems through API communication, which aligns perfectly with your requirement. Leveraging our knowledge in understanding and mapping client requirements through a semantic approach, we will create an Agent AI that is efficient and effective at identifying the right products for each quotation request. As a Google partner digital agency committed to delivering top quality services, you can trust us with not only building the AI but also managing its performance for seamless functionality. We know how valuable cost and timeline are to you and we guarantee not just affordable solutions but ones that won't compromise on quality or efficiency. Let's get started on making your quotation creation process smarter, faster and more accurate!