"Printflow" AI-Powered Print Shop Management System

@ZohaibRoy

⭐⭐⭐⭐⭐ Build an AI-Powered Print Shop Management System with Printflow ❇️ Hi My Friend, I hope you're doing well. I reviewed your project details and see you are looking for a full-stack developer to create Printflow. You have no need to look any further as Zohaib is here to help you! My team has completed 50+ similar projects for management systems. I will follow the detailed architecture PDF you provide and ensure a smooth process throughout the project. ➡️ Why Me? I can easily build your Printflow management system as I have 5 years of experience in full-stack development, specializing in Python, FastAPI, and PostgreSQL. My expertise includes Docker, API integration, and building Telegram bots. I also have a strong grip on integrating LLM APIs, ensuring all parts of your system work seamlessly together. ➡️ Let's have a quick chat to discuss your project in detail and I can show you samples of my previous work. Looking forward to discussing this with you! ➡️ Skills & Experience: ✅ Python 3.12+ ✅ FastAPI ✅ PostgreSQL ✅ Docker ✅ Docker Compose ✅ Telegram Bot API ✅ LLM API Integration ✅ OCR Document Processing ✅ Knowledge Graph Implementation ✅ API Development ✅ Unit Testing ✅ Project Documentation Waiting for your response! Best Regards, Zohaib

@Microlent

Hello, I am Dr. Rajesh Rolen, PhD in Computer Science & Engineering, with experience of over 20+ years in API Integration, Software Development, PostgreSQL, Full Stack Development, OCR, Python, Docker As a preferred freelancer in the top 1%, I have done 400+ projects here on freelancer.com, I have 4.9 ratings out of 5 on average, which showcases my quality of work and timely delivery. Key Highlights: - Free Hosting Support on the Cloud or any desired platform. - Free 3 months of post-delivery support to ensure that our client doesn’t face any challenges after the launch of the project. - Free Dedicated tester on projects to ensure quality delivery, so clients don’t need to act as a tester. - 10+ Years experience UI/UX team to ensure intuitive UI. Portfolio: https://www.freelancer.com/u/Microlent Please open the chat and send me a message, so we can have a more detailed discussion about the project to give you the project timeline and cost. Thank you for considering my services. I look forward to engaging in a productive conversation and understanding how I can be of assistance in bringing your project to life. Regards Rajesh Rolen

@sumitsthakur

I can help you build Printflow as a robust, phase-driven print shop management system based on your architecture details. With my strong background in Python, FastAPI, PostgreSQL, and LLM integrations, I am well-equipped to handle the backend services, the knowledge graph, and the AI-driven components. My approach follows your 11-phase plan precisely, starting with clean project scaffolding and the PostgreSQL database schema, moving through the inventory, production, and finance domains, and integrating Claude, the Jev decision SDK, the Telegram bot, and Paperless-ngx. I will ensure the code is modular, fully tested, and ready for you to run effortlessly with Docker Compose. Based on your requirements, I estimate completing this project within 6 weeks. I focus on writing clear code and communicating in plain English so you can easily understand and test the final product. Let's discuss your project and review the architecture PDF to get started.

@denisSolution

Hi, I'm Denis, a full-stack developer experienced in building systems combining inventory management, document processing, and AI workflows—exactly what Printflow needs. I understand your architecture: production, inventory, and finance layers synchronized through a knowledge graph, with Claude and Jev handling intelligence, and Telegram and Paperless as interfaces. I've built similar systems with reserved versus consumed inventory logic, LLM integrations for document understanding, and webhook-driven workflows. I'm comfortable using PostgreSQL graph tables—simpler than Neo4j and easier to maintain. My approach: I'll review your architecture PDF and clarify edge cases, then build the database schema and core services in parallel as separate FastAPI modules (inventory, production, finance). Once solid, I'll integrate the knowledge graph, expose Claude-safe endpoints, add Jev for decision functions, and build the Telegram bot and Paperless webhook. Testing and documentation happen throughout. Early discussion point: how should we handle document extraction confidence from Paperless? Using Jev for confidence scoring is smart, but we need to define when to auto-update inventory versus flag for review. I estimate 6-7 weeks full-time: 1 week scaffolding and schema, 2 weeks core services, 1 week knowledge graph and Claude endpoints, 1 week Jev integration, 1 week Telegram and Paperless, 1 week testing and documentation. I'll provide hourly rates once we align on specifics. I

@DeveloperStation

Hi, I've built LLM-backed tools that turn plain questions into safe database reads, most recently an internal system that encodes our own domain knowledge into a queryable assistant using Claude and OpenAI APIs. BD Automation: internal AI workflow tool On the knowledge graph, I'd push toward Postgres graph tables rather than Neo4j given your "simple to maintain" note. One database, one docker compose, less moving parts for you to run alone. Neo4j only earns its place at real scale, which a single print shop won't hit soon. One question so I scope Phase 8 right: does TypeSafe Jev have a Python SDK on PyPI, or will I wire it through their REST endpoints? That changes how I structure the decision module. We can start with Phase 1 and 2 as the first milestone so you only release once the schema and scaffolding run clean on your machine. Adil

@sparkbrains

Hi, I can build Printflow as a modular full-stack system following your architecture PDF, covering Production, Inventory, Finance/AP, AI, and integrations. Key Deliverables: ================= FastAPI backend with PostgreSQL/SQLAlchemy 14-step production and inventory workflows Reserved/consumed stock tracking and alerts Knowledge graph linking jobs, materials, suppliers and documents Claude integration for natural-language business queries Jev decision functions and Paperless-ngx OCR integration Telegram bot for owner queries Docker setup, automated tests and complete documentation Tech Stack: Python | FastAPI | PostgreSQL | SQLAlchemy | Docker | Claude | Jev | Telegram | Paperless-ngx Estimated Timeline: 6–8 weeks. Question: Could you share the architecture PDF so we can review the workflows and provide an accurate phase-wise estimate? Best regards, Manu The price mentioned is just a placeholder!

@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 Python, and similar tools. I have worked with pytorch, and tensorflow to develop DL models, .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. you can find all the application that I have developed for mobile and web applications devices please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@PINESCRIPTERR

Hi, I can build Printflow as a modular Python/FastAPI + PostgreSQL system, following your architecture PDF phase by phase while keeping the three domains cleanly separated and connected through shared identifiers and a maintainable knowledge layer. I can cover the inventory, production lifecycle, Finance/AP, Claude tool endpoints, Jev decision functions, Telegram bot, Paperless-ngx webhook/OCR workflow, Docker setup, migrations, automated tests and clear documentation for a non-technical owner. I would also keep the AI integrations behind controlled service interfaces so they can evolve without coupling the core business logic to a specific provider. Questione 1: Can you provide the architecture PDF first, including the expected 14-step production lifecycle states, domain relationships and any required knowledge-graph structure? Questione 2: For Paperless-ngx and Jev, will the provided documentation define the webhook payloads and SDK interfaces, or should those integration contracts be designed during the relevant phases? Regards, Houssame.

@rajat07me

This isn’t a simple CRUD app because the risky part is the handoff between production, inventory, finance, and AI decisions without the numbers drifting out of sync. I’d build it phase-first with a clean FastAPI service structure, strong PostgreSQL schema design, and explicit inventory rules for reserved vs consumed quantities before wiring in Claude, Jev, Telegram, and Paperless. I’ve worked on Python backends with Dockerized setups, API integrations, database-heavy workflows, and AI-powered features where non-technical owners needed the final system to be understandable and testable. For a system like Printflow, the quality of the schema, webhook handling, and read-only AI tool endpoints matters more than flashy AI prompts, because that is what keeps stock, invoices, and job status reliable. A small plus from my end: I’d keep the README and decisions log written in plain English so handover is easier for you. - Is your architecture PDF already opinionated about monolith vs separate services, or would you like me to choose the simplest maintainable structure? - For the knowledge graph, do you prefer staying fully inside PostgreSQL unless Neo4j is clearly justified? - For phase 1 delivery, do you want each phase reviewed and approved before the next starts?

@vishal1145

Your knowledge graph will fail under concurrent writes if you use a simple graph table in PostgreSQL without row-level locking. This creates race conditions when a job reserves material while a supplier delivery updates the same stock record. Quick questions - are you planning to run multiple Telegram bot instances or worker processes that could trigger simultaneous inventory updates? And what's your expected transaction volume during peak hours (jobs created per minute + supplier deliveries processed)? Here is the architectural approach: - POSTGRESQL: Implement advisory locks on inventory transactions and use SERIALIZABLE isolation for material reservation to prevent phantom reads during concurrent job creation. - FASTAPI + JEV: Build async endpoints with Jev decision functions cached in-memory to hit sub-50ms response times for stock availability checks called by Claude tools. - PAPERLESS-NGX WEBHOOK: Parse OCR'd supplier documents using structured output from Claude 3.5 Sonnet, validate extracted line items against purchase orders, then atomically update inventory and AP tables in a single transaction. I've built similar multi-domain systems for 2 manufacturing clients where real-time inventory accuracy was mission-critical. Let's schedule a 20-minute call to walk through your architecture PDF and confirm the graph schema design before I start Phase 1.

@C0RETECHIES

Hello, System understanding: Printflow manages a print shop via three interconnected domains - production/sales (job lifecycle from inquiry to payment), inventory (materials, stock, suppliers, reserved vs consumed quantities), and finance/AP (supplier invoices, payments, purchase costs). A knowledge graph links jobs, materials, suppliers, and documents, enabling natural‑language queries through Claude, fast decisions via Jev, and OCR‑driven updates from Paperless‑ngx. A Telegram bot lets the owner interact conversationally. Technical approach: We will scaffold a monorepo with FastAPI backend, Python‑Telegram‑Bot service, and a lightweight worker for Jev/Paperless webhooks. PostgreSQL will store relational data; we recommend using its built‑in graph table (pg_graph) for the knowledge graph to avoid extra infrastructure. Docker‑compose will orchestrate api, bot, worker, and Paperless‑ngx (if needed). Claude and Jev are called through exposed read‑only endpoints and webhook handlers. Core modules: 1) Inventory Service - material CRUD, stock reservation/consumption, reorder alerts. 2) Production Service - 14‑step job API, BOM calculation, inventory hand‑off at ORDER stage. 3) Finance/AP Service - invoice/PO linking, payment tracking. 4) Knowledge Graph - linking tables via graph edges, enabling traversal for Claude queries. 5) Claude Tool Endpoints - safe GET functions like get_open_jobs, check_material_availability. 6) Jev Decision Functions - Python module scoring supplier doc confidence, classifying alerts, wired to Paperless webhook. 7) Telegram Bot - receives messages, forwards to backend, returns Claude answers, includes /stock, /jobs, /invoices commands. Relevant systems: Bison360 - AI‑Powered ERP (Spring Boot, React, Flutter, PostgreSQL) - shows our experience building integrated inventory, sales, and finance modules with graph‑like traceability. AI‑Powered Slack Clarification Assistant - demonstrates n8n‑style workflow orchestration and LLM‑driven decision making, analogous to Jev/Claude integration. AI Newsletter & Blog Automation - highlights LLM‑based data extraction and structuring similar to Paperless‑ngx OCR processing. Implementation strategy: Start with Phase 1‑2 (scaffold, schema) to get a working DB and API skeleton. Iteratively add Inventory, then Production, then Finance services, each with unit tests. After core APIs are stable, implement the knowledge graph and Claude endpoints. Next, integrate Jev decision functions and Paperless webhook. Finally build the Telegram bot and write end‑to‑end tests. MVP‑first approach delivers a functional job‑tracker with inventory alerts by week 4, then layers AI and bot capabilities. Questions: 1) Should the knowledge graph be implemented solely with PostgreSQL pg_graph, or are you open to a lightweight Neo4j instance if performance demands it? 2) For the Jev integration, do you have existing Python SDK functions we should call, or will we need to wrap the provided TypeSafe Jev SDK ourselves? 3) Regarding Paperless‑ngx, will you provide a running instance for webhook testing, or should we assume a local Docker‑compose setup for development? Regards, Rohit

@kabirchy

Hi there, I understand you're looking for a full-stack developer to build an AI-powered print shop management system. I have extensive experience in the required technologies, including Python, FastAPI, Docker, and PostgreSQL, which will be crucial for developing a robust and efficient system. For the Printflow project, I propose using FastAPI for the backend to ensure high performance and easy integration with other services. Docker and Docker Compose will help in creating a consistent development and deployment environment. For the database, PostgreSQL will handle relational data, while Neo4j can be used for more complex, graph-based queries if needed. OCR capabilities can be integrated to automate document processing, enhancing the system's functionality. I'm excited about the opportunity to work on this innovative project and am confident in delivering a solution that meets your business needs. Best Regards, Khorshed Alam, RS Software

@muneeb6767

Printflow is a solid project to sink teeth into - three domains talking to each other through a knowledge graph, plus Claude and Jev sitting on top, is genuinely interesting architecture, not just another CRUD job tracker. Relevant experience: I built an invoice OCR pipeline (Tesseract + watchdog + Gmail SMTP) that auto-extracts data from incoming documents and updates records, which maps closely to your Paperless-ngx webhook + AP flow in Phase 10. I've also built a Telegram bot for financial record tracking with dual-user Excel logging, and run large PostgreSQL/Supabase pipelines with dedup + first-seen/last-seen logic across suppliers and inventory-style data. I've integrated the Gemini API into a production tool too, so wiring Claude in as a query layer over your own read-only endpoints isn't unfamiliar territory. Comfortable with FastAPI, SQLAlchemy, and Docker Compose for the backend/deployment shape you've described. I'd want to go through the architecture PDF fully before locking a phase-by-phase quote, but happy to start with Phases 1-3 (scaffolding, DB schema, inventory service) as a first milestone so you can see the approach before committing to the full 1-3 weeks. Two questions: is Jev's SDK/docs available upfront, or would that come once we reach Phase 8? And do you have a Paperless-ngx instance running already, or does that need setup too? Can share code samples from the OCR and Telegram bot work if useful. Open to a call to walk through your PDF.

@HamparProd

Printflow should keep production, inventory and finance deterministic, with AI used only where judgment or natural-language interaction adds value. I would build the core with Python 3.12, FastAPI, PostgreSQL, SQLAlchemy/Alembic and Docker Compose. Claude would receive safe read-only tools for owner queries, while Jev would handle bounded scoring/classification such as document confidence and inventory-alert severity. For material availability, reservations, stock movements and financial records, I would keep the calculations in normal tested application code rather than allow an AI model to modify business truth directly. For Paperless-ngx, document consumption would enqueue an asynchronous extraction task, then validate extracted supplier/items/amounts against the database before inventory/AP records are committed. I would also keep the initial knowledge graph inside PostgreSQL unless your architecture PDF demonstrates a real requirement for Neo4j. For the posted Freelancer budget, I recommend an initial CAD $1,500 milestone covering project scaffolding, database/migrations and the complete inventory-service foundation. Each following phase can then be accepted against the architecture specification before continuing. My relevant stack includes Python/FastAPI, PostgreSQL, Docker and LLM/API integrations, and I am comfortable implementing directly from a detailed architecture document and documenting the system for a non-technical owner.

@KarthikTechCon

Hello, I'm Karthik, a full-stack developer with over 15 years of experience in building robust applications. I specialize in Python, FastAPI, PostgreSQL, and Docker, making me well-suited for your Printflow project. ### Proposed Approach: 1. Phase 1-3: Scaffolding & Database Schema I'll create the project structure and design a PostgreSQL schema encompassing jobs, materials, and finances, ensuring clarity in reserved and consumed quantities. 2. Phase 4-5: Production & Finance Services I will develop APIs for the 14-step job lifecycle, material requirements, and supplier invoice management, linking them seamlessly. 3. Phase 6-8: Knowledge Graph & AI Integration Implement a knowledge graph for data relationships and integrate Claude and Jev for intelligent decision-making. 4. Phase 9-11: Telegram Bot & Paperless Integration Build a Telegram bot for easy interaction and set up OCR processing with Paperless-ngx for invoice management. ### Timeline & Budget: I estimate a timeline of 6-8 weeks for full completion. I can provide a detailed quote based on hours per phase upon discussion. I’m excited about the opportunity to work on Printflow and guide you throughout the process. Let’s connect to discuss your vision! Best, Karthik

@BarryCrouch

Hi there, Building a print shop management system like Printflow with multiple interconnected domains and AI integrations can often lead to complex data sync issues between inventory consumption and finance tracking if the database schema and service boundaries aren't cleanly structured from day one. My solution is to strictly implement a modular FastAPI backend with SQLAlchemy, leveraging PostgreSQL for relational data alongside simple graph tables to ensure your knowledge graph remains robust, maintainable, and seamlessly linked with Claude, Jev, and Paperless-ngx. Here are my questions: 1. Do you prefer using PostgreSQL graph tables or Neo4j for the knowledge graph implementation based on your familiarity with maintenance? 2. Should the Paperless-ngx webhook extraction rely primarily on Jev for document confidence scoring before hitting the LLM for structured data parsing? Drop me a message so we can get started right away.

@Hammadhassan21

Hey, Printflow will be much easier to scale if the core business logic is structured correctly from the start rather than treating everything as one large job tracking system. I’d build the database and service boundaries around the three key areas: inventory, production, and finance, making reservations, consumption, production stages, and financial records traceable before adding the knowledge graph and AI layer. I can work through the phases using Python/FastAPI, PostgreSQL, SQLAlchemy, Docker, Telegram, LLM integrations, and webhook driven document processing, with proper testing around each service and clear documentation for a non technical owner. I’d also keep AI tools read only where appropriate and make inventory and finance changes explicit and fully auditable. I can show you similar AI and LLM workflow examples in chat. Once I review the architecture PDF, I can identify any assumptions or conflicts and then provide a realistic phase by phase estimate and timeline based on the actual scope. Portfolio: https://www.freelancer.com/u/Hammadhassan21 Best regards, Hammad Hassan

@longngoc2307

==== Hi - Truong here ==== "AI-POWERED PRINT SHOP MANAGEMENT SYSTEM" - you need to connect production, inventory, and finance into one working system I would build Printflow in phases, starting with the FastAPI foundation, PostgreSQL structure, and core workflows before adding AI tools. The important part is keeping inventory, jobs, and supplier data consistent so automation gives reliable answers. I would structure the LLM, Telegram bot, OCR, and decision functions as separate services so each part can be tested and improved without breaking the system. Which parts of the architecture are already finalized, and should Phase 1 begin with the full database design or the API foundation? Looking forward to work with you.

@mickeysz

Hello, You gave reserved and consumed their own columns, which tells me you sense where this system lives or dies: the inventory numbers. If stock is a single balance that gets overwritten, concurrent deliveries, reservations and consumption race each other and the number drifts. Then "do we have enough material for all scheduled orders?" returns a wrong answer, and that question is the whole point of the AI. So every stock change is an immutable inventory_transaction row, receipt, reservation, consumption, release, and reserved, consumed and available are computed from the ledger. Correct under load, and auditable. That foundation is also what makes Claude safe. Claude never does the arithmetic itself, because LLMs miscount. It only calls your read-only endpoints, get_material_requirements and check_material_availability, which do the real math against the ledger. The model is the interface; the truth is SQL. Your Phase 7 design is exactly right. On Paperless, webhooks retry, so a delivery note processed twice would double-count stock. I make the handler idempotent on the document id, and use Jev's confidence score to route low-confidence reads to your review before they touch inventory or AP. I will also guide you through testing in plain English. My similar AI/LLM projects are attached. One question: does the graph need deep multi-hop traversal, or are the links mostly direct? If direct I keep it a Postgres edge table, so you run one database not two.