Custom MVP AI Chat Runtime Development

@infowider11

->> Custom AI Chat Runtime MVP Development <<- Hello, I have carefully reviewed your requirements and bring 10+ years of experience in web and mobile app development. I'll develop a secure, scalable AI chat runtime MVP with full source code ownership, editable prompt management, PDF intelligence, and a modular architecture that can easily evolve with future features. Key Features ➼ User Authentication ➼ AI Chat Assistant ➼ Prompt Mode Management ➼ PDF Upload & AI Query ➼ Conversation Export ➼ Admin Prompt Dashboard WITH 3 MONTHS FREE SUPPORT AFTER DEVELOPMENT LET'S CONNECT AND START YOUR PROJECT ASAP Regards, Shweta!!

@aqualeafitsolpl

Hi there, I have checked your requirements where you mentioned that you are looking for a developer to build a custom MVP AI chat runtime…Please invite me in chat so we can discuss in detail….

@Hrolgar

M1: Supabase schema, auth, and the prompt registry table with versioning, $320, 4 days. M2: chat runtime wired to Jedidiah, saved conversations, and the correction log tied to prompt versions, $370, 4 days. M3: PDF upload, chunking, embeddings, and Q&A over the extracted text, $340, 3 days. M4: admin panel plus repo and Supabase handover with docs, $245, 3 days. The part that decides whether this holds up over time is the prompt registry, not the chat UI. If the different modes for Jedidiah end up as string constants baked into code, every wording tweak needs a redeploy, and the correction log stops being useful because nobody can trace a fix back to which exact prompt version was running when the mistake happened. I'd model modes as rows in a Supabase table from day one, versioned, so the admin panel can edit and roll back live and the correction log references the exact prompt version each saved conversation used. Same thinking applies to the PDF side. Instead of stuffing extracted text straight into the context window, I'd chunk it and store embeddings in Supabase with pgvector, so Q&A over a document holds up whether it's five pages or two hundred, and nothing about the setup has to change later when the documents get bigger. Everything lands in your own GitHub repo and Supabase project from the first commit. No separate hosted backend to hand over later, no no-code platform holding the logic hostage. One thing worth knowing before I start: should the correction log just be a review trail for now, or does it need to feed corrections back into prompt tuning automatically. Changes how much structure I put around it in M1.

@zainalitariq245

I'll keep the proposal in your exact requested format. Greetings, You need a dependable long-term development partner who can consistently deliver business websites, WordPress solutions, redesigns, and ongoing maintenance for your client projects with reliable communication and quality. We will build this with: custom business websites, WordPress development, landing pages, eCommerce stores, website redesigns, and ongoing maintenance support. A couple of questions before I provide a detailed plan: Do you have a preferred tech stack or page builder for most client projects, such as Elementor, Bricks, or custom WordPress? Will developers be expected to work directly with your clients, or will all communication go through your studio? Portfolio: freelancer.pk/u/zainalitariq245 Based on your requirements, I can suggest the most scalable approach and provide timeline and cost estimate after discussion. Looking forward to discussing the details. Best regards, Zain Ali

@MushtaqMagri

As a seasoned full-stack developer with significant experience in AI chatbot development, I can provide you with the specialized skills you need to bring your unique project to life.I will use react.

@jcrbahia

Jedidiah as the core assistant with swappable prompt modes in an editable registry, not one giant hard-coded prompt — that's the right architecture for something you plan to keep extending. - Auth and data on Supabase (Auth, Postgres, Storage) with RLS scoped per user from the first commit; repo lives in your GitHub, nothing withheld or hidden. - Prompt registry as a Postgres table (mode, system prompt, model params) surfaced via the admin page, so new modes are rows, not redeploys. For the correction log — are corrections tied to specific messages/turns, or logged as free-form notes per session? That shapes the schema. - PDF pipeline: upload to Supabase Storage, server-side text extraction, chunking for retrieval, and evidence labels referencing source pages; Markdown export pulled straight from the conversation table, no separate formatting step. Delivery in exactly 2 weeks for the milestone as defined: login, chat, mode selector, save conversation, correction log, PDF upload and Q&A, export. Treat this amount as an initial, orientative reference for the scope as described, not a final price — we'll confirm the exact number once we walk through the remaining open points, starting with the correction log format. Happy to do a quick call here on Freelancer to align on that, and feel free to check my profile and portfolio meanwhile.

@Eliteinno

Hey, I really like that you're explicitly avoiding hard-coded prompts and want an editable registry. I'd set up a dedicated table in Supabase Postgres for your prompt modes, making them super easy to manage and swap out from the admin page. Getting the PDF text extraction and accurate question-answering with those 'basic evidence labels' just right is often the trickiest part, but I've got solid strategies for that. Are you thinking of starting with a few specific prompt modes for Jedidiah, or will that be defined later?

@mughiraaa

Hello, Your vision for this MVP is clear, and I appreciate the focus on ownership and future growth. I have strong experience with Next, React, TypeScript, Supabase, AI integrations, document processing, and secure authentication. I can deliver clean, organized code that stays entirely under your GitHub and Supabase accounts. I would love to schedule a quick discussion to review the first milestone and future roadmap. I am confident we can create a solid foundation that is easy to extend as your platform grows. I will share my portfolio in chat I look forward to hear from you. Thanks Best Regards, Mughira

@youssefhachicha

Hi, hope you are doing well. I can build the MVP AI chat runtime for Jedidiah using Next js React TypeScript Supabase Auth Supabase Postgres Supabase Storage and OpenAI API with a structure that you fully own from day one. I understand this is not a generic chatbot or no code builder. My approach will be to create a clean foundation with user login main chat mode selector editable prompt registry saved conversations correction logs file and image upload PDF upload PDF text extraction PDF Q and A evidence labels Markdown export and admin prompt management. Prompts and modes will be stored in Supabase and editable from the admin page, not hard coded into one giant prompt. The AI provider layer can also be built so OpenAI can be swapped later if needed. All code will be pushed to your GitHub repo from the start and all data will live in your Supabase account. Best regards Youssef.

@atesicfl

With over a decade of experience in both backend and frontend development, I firmly believe I am the right freelancer for your Custom MVP AI Chat Runtime project. My proficiency in the MERN stack, Ruby On Rails, and ASP.NET falls perfectly in line with your preferred tech stack. I assure you that from day one, all code will be owned by you on your GitHub. Plus, as an open-source contributor myself, I truly understand the significance of code ownership and the freedom to build upon it. Aside from my technical acumen, I am known for my meticulous problem-solving abilities within tight deadlines without compromising quality. My agile approach aligns well with your project requirement of starting simple and stable before incorporating further features. Hence, I am not only proficient in meeting your immediate needs but also committed to creating a solid foundation that can be built upon seamlessly for future augmentations. It'd be an honor to work with you on this project and I look forward to putting my skills into action for its successful completion.

@mojjammil

I've built a few chat interfaces where the prompt management was the tricky part—if the prompts are editable in the database, you have to handle versioning carefully so that old conversations still render correctly even after you've updated a prompt. I'd start by setting up the Supabase tables for users, conversations, messages, prompts, and corrections, then wire up the authentication layer first so you have a clean login flow. After that, I'd implement the chat core with the mode selector and PDF upload side-by-side since both rely on the same message-handling logic. The main risk is PDF extraction—some PDFs have embedded text, others are scanned images, and we'd need to decide early whether to support OCR or just handle text-based PDFs for the MVP. For the editable prompts, do you want a simple text area in the admin panel, or do you need version history and the ability to roll back? Also, should the PDF question-answering use the same AI provider, or are you open to a separate embedding/retrieval flow? If we're aligned, I can outline the implementation phases before kickoff. Best regards Mojjammil

@k1ng440

A custom chat runtime means you're building the orchestration layer yourself, not wrapping an off-the-shelf framework. The parts that usually bite are streaming state, tool-call handling, and keeping latency low once real traffic hits. I've built systems around exactly this kind of problem. At Coinread I ran 20+ microservices and got response times under 100ms using Go and gRPC, and I've architected a platform juggling 150+ external service integrations without the whole thing falling over. For an MVP, I'd keep the runtime lean but structured so it doesn't need a rewrite the moment you add features. Streaming responses, clean tool interfaces, and observability baked in from day one so you can actually see what's slow. Go or Node both work well here depending on what you're already leaning toward. To scope this properly, what does "custom runtime" mean for you specifically: is this about model routing, tool orchestration, memory, or all three?

@yuan38

Hi, I saw your project and think I can deliver what you need. Let's build a system so smart that your future self sends us both a thank-you note. I understand what you want in this project. I will give frequent updates and the final result that matches your expectations. I am an expert with 10 years of experience in Backend Development, Frontend Development, AI Chatbot Development, Next.js. I have helped many clients bring ideas to life and reach their goals. Visit my profile to check my latest work and read short client reviews. Please reach out in chat so we can align on your needs and goals. Thank you, Yuan

@vladang

What you're describing sounds less like a chatbot and more like the foundation of a long-term AI workspace, so I'd keep the first version intentionally narrow and make sure the architecture stays easy to evolve. I'd start by setting up the GitHub repository under your account and connecting everything directly to your Supabase project from day one. The chat runtime, prompt registry, conversations, corrections, and file handling would all be separate entities rather than being buried inside one giant system prompt. That makes prompt modes editable, versionable, and much easier to expand later. For the PDF workflow, I'd extract and store document content, then attach document context only when needed so users can chat normally or ask questions against uploaded files without mixing concerns. I'd also build the AI layer behind a provider abstraction so OpenAI can be swapped later without rewriting the app. The first milestone you outlined is realistic within the 2–4 week window and aligns well with a stable MVP approach. One thing I'd like to clarify: should prompt modes be selectable manually only, or should Jedidiah be able to switch modes automatically based on context as the product evolves? I'm ready to start building this foundation.

@Aaleen110

I understand you require a custom MVP AI chat runtime, specifically for an assistant named Jedidiah, featuring multiple prompt modes and the ability to interact with uploaded PDFs. I've built similar backends for AI-driven applications, including a system that successfully processed and queried large document repositories for a legal tech startup, reducing information retrieval time by 80%. My development approach will involve building a Python backend using Flask, integrating LangChain for prompt management and PDF processing (PyMuPDF for extraction, FAISS for vector storage), and utilizing PostgreSQL for user data and conversation history. The frontend will be built with React Native for cross-platform compatibility. This will provide you with full code ownership and a foundation for future expansion. How will the "basic evidence labels" be structured and displayed within the UI? Ready to start as soon as you confirm scope.

@jeremiasg17

Hello! I’ve built a custom AI chat system with similar requirements, focusing on performance and scalability. One project resulted in a 30% increase in user engagement through tailored prompt management, which I’d be happy to show you in chat. For your MVP, I’d approach it by breaking down the features into modular components, ensuring that each part—like user login and the multi-channel selector—is independently manageable and easily extendable. I’m particularly interested in how you envision users interacting with the prompt modes. What specific capabilities do you want for managing the editable prompt registry? If you’re open, I can share the similar build and we can see if it fits.

@natanr28

Hi, The most important architectural decision for this MVP isn't the chat interface. It's keeping prompts, conversations, files, and AI providers independent from each other so the application can evolve without accumulating technical debt. I would build the runtime around modular services instead of a single orchestrator prompt. Prompt modes would be stored in the database and managed through the admin interface, making them editable without code changes. The chat layer would consume those prompts while remaining compatible with OpenAI today and other providers in the future. Your ownership requirements also align with how I prefer to work. The GitHub repository, Supabase project, authentication, database, and storage would all be under your accounts from day one, with no hidden infrastructure or vendor lock-in. For the first milestone, I'd focus on delivering a stable foundation that includes authentication, AI chat, prompt mode selection, conversation persistence, correction logging, PDF upload with text extraction, retrieval-based question answering, Markdown export, and an admin interface for prompt management before introducing additional features. I'm available to start immediately and would be glad to discuss the architecture in more detail.

@TechizeBuilder

Hi, I'm excited about your project Custom MVP AI Chat Runtime Development because successful social platforms require both excellent user experience and scalable technology. With strong expertise in Backend Development, Frontend Development, I can develop a secure, high-performance application featuring user authentication, content sharing, real-time messaging, media uploads, moderation tools, and analytics. My focus is on building a platform that encourages user engagement, supports long-term growth, and delivers a smooth experience across all devices. I look forward to working with you.

@libnim3

Hello! I'm a backend engineer with experience building AI-powered applications, scalable APIs, and production systems. My expertise includes Rust, Go, Python, LLM integration, RAG workflows, backend architecture, and designing maintainable AI services with clean, extensible code. For your MVP, I would build a solid foundation with secure authentication, an AI chat runtime, editable prompt management, conversation and correction storage, PDF processing with question answering, and a flexible architecture that keeps all code and data under your GitHub and Supabase accounts. The focus will be on delivering a stable, well-structured MVP that is easy to extend as your product evolves. I'd be happy to discuss your requirements and help build a foundation you can confidently grow over time.