AI deployment with Backend

@extreamcode

Hi, Your project for designing an LLM orchestrator embedded in your insurance website strikes me as a pivotal innovation that blends deep AI integration with seamless user experience. With my extensive background in Python ML frameworks like TensorFlow and scikit-learn, plus building APIs with Django and Docker deployments on AWS, I can help architect and deliver your end-to-end AI workflow. I understand the critical need for handling customer data streams, risk-level predictions, and policy recommendations accurately, alongside a React-friendly REST API and an admin dashboard for underwriting controls. I’ve developed similar risk scoring systems, focusing on reproducible pipelines, Dockerized deployments, and smooth product hand-offs. I’ve shared an initial estimate based on your description, and once we go over a few technical or functional details, I’ll confirm the exact cost and delivery schedule. Let’s discuss your preferred timelines and PoC milestones so I can tailor the roadmap precisely. Could you share more details on the preferred data schema for the customer master DB and claims history to ensure seamless integration? Thanks, Asad

@Julian29

Hello, I have 10+ years of experience, I’ve built multiple AI-powered decisioning systems and backend platforms, including risk scoring, policy recommendation, and automated workflow orchestration. I understand you need a LOB-aware LLM orchestrator and risk engine embedded into your insurance website, with a clean REST API, supervised risk scoring, policy recommendation, underwriter alerts, and an admin dashboard. What I will deliver LLM Orchestrator design with tool-calling patterns, structured forms, and citations Data ingestion from customer master DB, policy admin, claims history, and market datasets Supervised risk models (TensorFlow/PyTorch/scikit-learn) with a reproducible training pipeline Policy recommendation engine with clear explainability and underwriter flags REST/JSON API for your React frontend Lightweight Python admin dashboard for thresholds, retraining, and monitoring Dockerised API ready for local and AWS Elastic Beanstalk deployment Staging demo showing full quote flow and underwriter alert on high-risk input Hand-over video + setup guide Key Highlights LOB differentiation (Personal Auto, Commercial, Travel, Life) built into the workflow Real-time risk scoring and policy suggestion Explainability score for underwriter review I have some questions about your data schema and underwriting rules, in chat as I have some queries to ask regarding the project to proceed further. Awaiting your positive response. Thanks

@rohan3188

Hello, I've reviewed your requirements and have worked on similar projects before. With my experience and skills, I can complete your project to your satisfaction. Please contact me via chat to discuss the details. Thank you.

@corpmember29

I HAVE DESIGNED AND DELIVERED AI-DRIVEN DECISIONING & RISK-SCORING PLATFORMS FOR INSURANCE AND FINTECH THAT OPERATE IN REAL PRODUCTION ENVIRONMENTS ? I can design and implement an end-to-end LLM-orchestrated risk and quoting engine tailored to multi-LOB insurance workflows. The solution will embed seamlessly into your existing website while remaining modular, auditable, and production-ready. Core Features • LLM Orchestrator with tool-calling to Customer Master DB, Policy Admin, and Claims systems • LOB-aware workflows (Personal Auto, Commercial, Travel, Life) with structured forms • Supervised risk-scoring models trained on historical claims data • Automated quote & limit recommendations with explainability scores • High-risk flagging and underwriter alerts • Vector DB (Pinecone/Weaviate) for contextual reasoning and citations • REST/JSON API for React frontend + Python admin dashboard • Fully dockerised services deployable on AWS Elastic Beanstalk User Roles • Visitor / Prospect – guided quoting via AI assistant • Underwriter – review risk flags and explanations • Admin / Manager – adjust thresholds, retrain models, monitor outputs Deliverables • Complete source code ownership (models, APIs, middleware, infra) • Reproducible training pipelines & data schema docs • Dockerised APIs + staging demo of full quote flow • Handover documentation and walkthrough video

@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

@mrresearcher99

Hi there, I’ve reviewed your PHP project requirements and would be glad to help. With 5+ years of experience in PHP and backend development, I specialize in creating secure, scalable, and high-performing web applications using modern frameworks like Laravel and CodeIgniter. I’ll begin with a clear development plan, share regular progress updates, and ensure the final product is well-tested and optimized for performance and security. Let’s connect to discuss your project goals — I’m ready to get started! Best, Bhargav PHP Developer | Laravel & Backend Expert

@pinkeegupta

Hello I have read your requirements and I am sure I will be able to help you. Please message me so that we will have detail technical discussion. I have 9+ years of combined experience in Mobile Application development in Native on Android Java, kotlin and IOS Swift, and For Hybrid Cross platform on Flutter Dart & React- Native and for web and backend on react js and node js, Python Django , java spring boot and php CodeIgniter mvc. Please consider me and initiate a chat for further detailed discussion. Regards, Anju Logical Soft Tech Pvt Ltd, Indore(M.P)

@ixorawebmob

Hello, I’ve gone through your project details, and this is something I can definitely help you with. With over 10 years of experience in developing AI solutions, particularly in insurance tech, I’m well-versed in orchestrating complex workflows. My expertise includes integrating various systems, training supervised risk models, and building robust APIs. I focus on clean architecture and scalable solutions to ensure your project runs smoothly from inception to deployment. I can set up the infrastructure you need, ensuring that your AI layer seamlessly interacts with your existing customer master DB and incorporates historical claims data for real-time predictions. This will include embedding an AI chat assistant that enhances user experience while managing backend logic. Here is my portfolio: https://www.freelancer.in/u/ixorawebmob I’m keen to understand more specifics to ensure the best approach. Here’s my question: Could you outline your expectations for the data streams and how frequently they need to be updated to ensure accuracy? Let’s discuss over chat! Regards, Arpit Jaiswal

@johnallenvillan1

Hi there, I am excited about the opportunity to work on integrating AI into your insurance website to enhance customer experience and risk assessment. With my expertise in Python and machine learning tools like TensorFlow, PyTorch, and scikit-learn, I will design and deploy a solution that predicts individual risk levels, recommends policies, flags high-risk clients, and provides a seamless REST/JSON API and a Python-based admin dashboard. I will ensure a reproducible training pipeline, Dockerized API, staging domain demo, and detailed setup guide. Looking forward to discussing timelines and milestones.

@manojmalviya93

Hi, I have 10+ years of experience building AI driven decisioning platforms with a strong focus on Python based ML systems, LLM orchestration, and production APIs. I have worked on similar insurance and risk scoring systems and can design and implement an end to end LLM aware architecture that integrates customer data, policy systems, and claims history to deliver real time risk prediction, automated quoting, underwriter alerts, and a Dockerised REST API ready for AWS deployment. I would be glad to share the similar process for this project from my portfolio and discuss the technical direction, model choices, tool calling patterns, and PoC milestones in a focused call. Thanks and regards, Manoj

@Azursol

Hello Dalbir! I’m excited about the opportunity to help with your project. Based on your requirements, I believe my expertise in PHP, JavaScript, Python, OpenAI, Django aligns perfectly with your needs. How I Will Build It: I will approach your project with a structured, goal-oriented method. Using my experience in PHP, JavaScript, Python, Django, Software Architecture, Machine Learning (ML), Data Science, Docker, REST API, OpenAI, I’ll deliver a solution that not only meets your expectations but is also scalable, efficient, and cleanly coded. I ensure seamless integration, full responsiveness, and a strong focus on performance and user experience. Why Choose Me: - 10 years of experience delivering high-quality web and software projects - Deep understanding of PHP, JavaScript, Python, OpenAI, Django and related technologies - Strong communication and collaboration skills - A proven track record — check out my freelancer portfolio. - I’m available for a call to discuss your project in more detail - Committed to delivering results on time, every time Availability: I can start immediately and complete this task within the expected timeframe. Looking forward to working with you, Dalbir! Best regards, Ali Zahid Canada

@webmasters486

Hey, I’ve reviewed your project and understand you’re looking to design a sophisticated, LOB-aware AI workflow for your insurance website that integrates customer, policy, and historical claim data to predict risk, generate quotes, and assist underwriters. The focus is on an end-to-end AI layer that handles real-time applications, recommends policies, flags high-risk cases with explainability, and exposes results via a REST API for your React frontend while providing an admin dashboard for threshold adjustments and model retraining. I can help architect and implement a Python-based solution using TensorFlow, PyTorch, or scikit-learn for supervised risk models, coupled with a chatbot layer via Rasa or fine-tuned OpenAI models for front-end interactions. The setup will include reproducible training pipelines, Dockerised APIs for local and AWS Elastic Beanstalk deployment, clear data-schema documentation, and a lightweight Python admin dashboard. Citations and references will be incorporated for transparency and audit purposes. You’ll receive a working staging demo showing full quote flow, high-risk alerts to underwriters, and concise handover materials including a video and written guide. Let’s connect so I can outline PoC milestones, data ingestion patterns, and LOB-specific workflows to get this complex automation running reliably. Best regards, Muhammad Adil Portfolio: https://www.freelancer.com/u/webmasters486

@quan9824

With my extensive background in full-stack development and AI systems, I bring a comprehensive skill set to your project, encompassing both the web application design and the implementation of complex machine learning models. Drawing on my varied experience, I am confident in my ability to fulfill each aspect of your project’s requirements. One of the key strengths that I bring is my focus on not only creating a functioning system but also on its performance and user experience. In this case particularly, I understand how critical it is to provide accurate risk predictions almost instantaneously as soon as an application is submitted. Having transferred real-time data into actionable insights using machine learning models many times before, I believe I am well-suited to your task. Moreover, having worked extensively with similar kinds of processes as we can see here from my experience, including building web applications with backend infrastructure for companies to process intricate information and making them accessible through APIs,Citations, Structured Forms etc. My adaptability to new technologies combined with sound problem-solving skills ensure a smooth creation process. Finally, I have a 100% job completion rate and commit to delivering quality work within set deadlines - values that align perfectly with what you are seeking for your project.

@KarthikTechCon

Hello, I’m Karthik, an AI & backend architect with 10+ years of experience building insurance risk-scoring systems, LLM orchestration layers, and production ML APIs. What I’ll deliver: ✔ LOB-aware AI workflow (Auto, Commercial, Travel, Life) with tool-calling ✔ Integration with customer DB, policy admin, claims history, and market data ✔ Supervised risk prediction models with explanation scores for underwriters ✔ Automatic policy & premium recommendations ✔ High-risk alerts routed to underwriting with clear reasoning ✔ REST/JSON API for your React frontend ✔ Python admin dashboard to adjust thresholds and retrain models Architecture: Reproducible ML training pipeline with schema docs Dockerized API deployable locally and on AWS Elastic Beanstalk End-to-end demo: application → quote → policy → underwriter alert Clean documentation + handover video I focus on explainable, insurer-safe AI that fits real production workflows—not demos. Happy to discuss milestones and share relevant risk automation work. Karthik 10+ Years | AI Orchestration | Insurance ML | Python | Backend Systems

@iwebphpdeveloper

Hello, With 15 years of full-stack and AI-driven systems experience, I can design and deliver an end-to-end LLM-orchestrated insurance platform that connects your customer master DB, policy admin, claims history, and market data into a single decision engine. I will implement a LOB-aware architecture (P&C auto, commercial, travel, life) with tool-calling, vector search, and structured forms to guide prospects from chat or form input through quoting, risk scoring, and policy recommendation. The solution will include supervised ML models (TensorFlow, PyTorch, or scikit-learn), a Dockerised REST API for your React frontend, and a Python admin dashboard for underwriter controls and retraining. You’ll receive a reproducible pipeline, AWS-ready deployment, a live PoC on staging, and full documentation with citations and handover. Regards, Abhijeet

@NEHABHAT92

As a seasoned web and mobile app developer, with a strong background in JavaScript and PHP, I am perfectly suited for your project. For over 9 years, I have honed my skills in E-commerce and CMS based website development and your LLM orchestrator project aligns well with my expertise. Utilizing tools like TensorFlow, PyTorch, scikit-learn, Rasa and OpenAI models, I can create a custom AI layer for your website that seamlessly integrates with various systems. In particular, my experience building and deploying dockerized APIs on platforms like AWS Elastic Beanstalk will ensure a smooth deployment. Moreover, I bring to the table extensive experience in building end-to-end solutions. I understand the need to gather data from different streams and have it processed within your architecture. Drawing insights from historical claim records, real-time customer applications, and market-trend datasets to make accurate predictions is an area where I excel. Not only can I meet all your requirements - developing the necessary infrastructure, integrating relevant databases & models and crafting a REST/JSON API, but I'll also go the extra mile by providing a reproducible training pipeline with comprehensive documentation, an underwriter alert system using clear explanations for high-risk clients and an admin dashboard for easy management. Reiterated by testimonials from satisfied clients attesting to my effective cost strategy, cross-browser compatibility, after-delivery sup

@ssquare489

I am Sumit Joshi from Sacesta Technologies. I can design and ship your LLM orchestrator layer that identifies existing customers via Customer Master and Policy Admin, routes new quotes by LOB, and runs risk scoring plus recommendation with explainable outputs through a clean REST JSON API. Recommended architecture • Orchestrator: tool-calling router with guarded JSON schemas, retries, and audit logs • Data: Customer Master DB, Policy Admin, real-time applications stream, claims history, market datasets • ML: supervised risk model with probability calibration and explainability using SHAP • RAG: vector DB for underwriting guidelines, FAQs, and product rules with strict retrieval filters • Chat and forms: Rasa custom actions or model-based assistant that calls the same tools • Deploy: Dockerized Python API for local and AWS Elastic Beanstalk Questions • Which system is the back-office rating and policy binding target, and what payload schema does it require for quote and bind? • Do you need model retraining on a schedule, or only on-demand with approval and version rollback? Relevant work • Secure AI Insight Platform: role-based RAG, exports, and audit-friendly workflows • AI Productivity Suite: ingestion pipelines, structured outputs, and dashboard controls Regards, Sumit Joshi

@citijayamala

I have successfully developed AI agents for social media management (Meta/Facebook), customer support, lead generation, and appointment booking—all powered by n8n and integrated seamlessly with existing business systems. My expertise lies in designing end-to-end automation workflows that combine n8n orchestration with advanced AI models such as OpenAI GPT-4, Claude,Vapi, LLaMA, and other state-of-the-art LLMs, enabling intelligent, context-aware, and scalable business solutions. Sure, I can handle your project on deploying the AI agent with Backend with Python and LLM orchestrator, integrating with various systems. Kindly please connect in chat to discuss. I specialize in: • n8n Workflow Development: API integrations, webhook automation, multi-step workflows, and data transformations. • AI Agent Design: Conversational models, NLP/NLU pipelines, prompt engineering, and fine-tuning for domain-specific tasks. • Cross-Platform Integration: Social media APIs (Meta/Facebook, Instagram, LinkedIn), CRM systems, email marketing platforms, and custom backend systems. • Automation Infrastructure: Self-hosted n8n on Docker/VPS, cloud deployments, API authentication (OAuth, tokens), and data security best practices. • Advanced Use Cases: Intelligent lead qualification, AI-driven customer engagement, automated scheduling, and content generation pipelines. Whether it’s creating a fully automated sales funnel, AI-powered content research tool, or real-time customer support agent.

@faisal9263

Hello, I understand you need a complete LLM-driven insurance workflow that integrates customer master data, policy admin, and multi-LOB quoting while delivering real-time risk scoring, recommendations, and underwriter alerts through a scalable AI architecture. I have strong expertise in Python, LLM orchestration, ML risk modeling, API design, and insurance decision systems. I will design the LOB-aware workflow, set up infrastructure, models, vector DB, and middleware, build a reproducible training pipeline, implement tool-calling and structured forms, develop a Dockerised REST API with dashboard controls, integrate with your React front end, and deliver a working PoC with documentation and citations. You will receive accurate, reliable, and timely delivery. Please message me to discuss milestones and start.