I need help comparing two sets of genealogy/archive files. I have: A “Primary Set” of files, all located in one folder. A “Secondary Set” of files, located across multiple folders and subfolders. The goal is to identify all files in the Secondary Set that are NOT already present in the Primary Set, and then either list them and copy them into a new folder. Important requirements: Please compare files by file contents using a hash/checksum method, not just by filename. The Secondary Set should be scanned recursively, including all subfolders. Please do not delete, rename, or alter any original files. Please create a new folder called something like “Secondary_Not_In_Primary” containing only the files from the Secondary Set that are not duplicates of files in the Primary Set. Please also provide a CSV or Excel report listing: original file path in the Secondary Set filename file size file hash/checksum whether the file was copied to the new folder Please briefly describe the tool or method used, such as Python, PowerShell, Beyond Compare, FreeFileSync, or another reliable file comparison tool. This should be a small fixed-price project for someone experienced with file comparison, deduplication, or data cleanup.

We are looking for a highly capable AI consultant with a strong technical background in software development, AI-assisted workflows, and research. The ideal candidate is someone who understands modern AI tools, can quickly evaluate information for accuracy, and can help accelerate development, documentation, and decision-making across a variety of projects. * Utilize AI tools such as Claude, ChatGPT, and other leading platforms to support research, analysis, and development * Verify information, identify reliable sources, and distinguish between speculation and fact * Assist with software development, debugging, and technical problem-solving * Build scripts, automations, prototypes, and internal tools as needed * Help organize complex information and knowledge systems, including work within Obsidian * Translate ideas and concepts into actionable plans, technical documentation, and working solutions * Collaborate on a wide range of technical, operational, and strategic projects Qualifications * Strong software development experience * Proficiency with modern programming languages such as Python, JavaScript/TypeScript, or similar * Extensive experience using AI tools, including Claude, ChatGPT, Cursor, and related technologies * Ability to critically evaluate information and conduct high-quality research * Strong understanding of AI concepts, terminology, and emerging technologies * Excellent written and verbal communication skills * Comfortable working independently and navigating ambiguity

I'm looking for an experienced AI automation engineer to build an MVP for an internal AI-powered M&A Deal Intelligence platform. Project Goal I want to build a system that helps my M&A advisory firm identify acquisition opportunities, research businesses and owners, and prepare me for outreach—all while integrating with our existing Zoho CRM. MVP Requirements - Find businesses from selected public sources using lawful methods. - Gather company information (website, industry, location, products/services, leadership, estimated size, etc.). - Research owners and decision-makers using publicly available sources (company websites, LinkedIn, news, press releases, interviews, social media, public business records where appropriate, etc.). - Generate an AI briefing before I contact a prospect that includes: - Company summary - Owner background - Personalized conversation starters - Suggested questions - Potential acquisition opportunities - Risks or notable findings - Automatically create or update records in Zoho CRM with the research and AI summaries. - Be designed so additional data sources, automations, and AI capabilities can be added over time. Preferred Skills - AI agents - Python - OpenAI API (or similar LLMs) - Web scraping - Playwright - Apify - n8n or similar automation platforms - API integrations - Zoho CRM integrations - Experience building AI research or deal sourcing tools is a major plus. When Applying Please include: - Examples of similar AI automation or research systems you've built. - The technology stack you'd recommend. - How you'd approach this project. I'm looking for a long-term technical partner to continue expanding this into a comprehensive AI platform for our M&A advisory business if the initial project is successful.

We are looking for a hands-on Forward Deployed AI Engineer to help build practical AI systems This is not a pure backend role and not a strategy-only consulting role. You will work close to end users, understand how their workflows actually operate, and then build AI-enabled tools that solve specific business problems. The ideal person is a strong software engineer who is comfortable with ambiguity, can communicate clearly with non-technical stakeholders, and can take an AI prototype from idea to something reliable and usable. What you will do - Learn the business workflows, systems, data, and constraints. - Build AI applications using Claude or similar large language models. - Use the right mix of prompting, retrieval, tool use, agents, and workflow automation. - Own delivery from scoping through prototype, testing, hardening, and handoff. - Create evaluations to determine whether the system is accurate, reliable, and safe enough to use. - Translate between domain experts and technical implementation. - Work carefully with sensitive or regulated data. - Document what you build so it can be maintained and reused. What we are looking for - Strong Python engineering skills. - Hands-on experience building with LLMs, preferably Claude or the Anthropic API. - Experience with RAG, structured prompting, tool use, evaluation, or agentic workflows. - Ability to operate independently in a messy, ambiguous environment. - Strong communication skills with both technical and non-technical stakeholders. - Track record of shipping working software, not just demos. - Comfort working with real-world data, integrations, and imperfect requirements. Helpful but not required - Prior forward deployed engineering, solutions engineering, or technical consulting experience. - Experience building AI tools for enterprise customers. - Experience in regulated or sensitive-data environments. - Familiarity with validation, auditability, traceability, or compliance-oriented workflows.

Job Description: We are seeking an advanced development partner or agency to architect and deploy a secure, high-availability AI automation platform that bridges modern intelligent agents with our existing legacy infrastructure.The core of this project requires building autonomous AI agents and dynamic RAG (Retrieval-Augmented Generation) pipelines for semantic search, which must securely interface with our backend databases and legacy applications.You will lead the end-to-end development, from writing robust backend APIs and designing a responsive React JS frontend, to configuring the underlying Linux servers and automated CI/CD pipelines. Key Responsibilities: Build custom AI agents and chatbots using advanced LLM API integrations and Model Context Protocol (MCP) tooling.Develop custom web crawlers to securely ingest, index, and structure big data into high-availability databases.Modernize and migrate legacy software components (including Classic ASP, PHP, and Java) into a modern TypeScript and Node.js microservices architecture.Implement workflow automations via Zapier/Make and deeply integrate third-party systems like Salesforce, Odoo ERP, Twilio, and Stripe payments.Set up robust DevOps practices, including automated QA testing, Linux server hardening, and comprehensive monitoring/observability metrics. Required Skills & Tech Stack: AI & Automation: LLM APIs, RAG, Semantic Search, Voice/Transcription, Zapier, Make.com.Core Languages: Python, Node.js, TypeScript, PHP, Java, Classic ASP.Frontend/CMS: React JS, Modern JS Frameworks, WordPress.Data & Infrastructure: Big Data engineering, advanced web scraping, Linux/Mail server administration, VMware alternatives, CI/CD pipelines, Networking & Security.Integrations: Salesforce, Odoo, Twilio, Google Workspace APIs.Web3 (Plus): Solidity, Smart Contracts, Token operations. Project Scope & Deliverables: Size: Large-scale enterprise migration and AI upgrade.Deliverables: Fully deployed AI workflows, a modern user dashboard, migration of legacy core features, and documented DevOps infrastructure.Experience Level: Expert.Budget Strategy: Hourly or fixed-price milestone contract.

About Us Paragon International, Inc. is a U.S.-based manufacturer of commercial concession equipment and food service products. We receive purchase orders from customers such as Amazon, Home Depot, distributors, school systems, and other commercial customers. Orders arrive by email in many different formats, including PDFs, Word documents, Excel spreadsheets, scanned documents, and occasionally photographed purchase orders. We are looking for an experienced AI Automation Engineer to design and build a production-ready system that automates our entire order intake process. This is not a simple chatbot project. We need someone who has successfully built business automation systems that combine AI, OCR, document processing, APIs, and workflow automation. Project Overview The system will monitor one or more Gmail inboxes continuously and automatically process incoming emails and attachments. The workflow should: * Monitor Gmail 24/7 for new incoming emails. * Download all attachments automatically. * Read: * PDF files * Microsoft Word documents * Excel spreadsheets * Scanned PDFs * Image files (JPG, PNG, TIFF, etc.) * Photographs of purchase orders * Use OCR when required. * Use AI to determine whether the email is: * Purchase Order * Quote Request * Cancellation * Return/RMA * Customer Inquiry * Other * Identify the customer automatically. * Extract all order information into a standardized data structure. * Detect duplicate purchase orders. * Automatically print valid purchase orders to our network printer. * Save documents into organized folders. * Rename files using a consistent naming convention. * Move processed emails into Gmail folders/labels. * Generate logs for auditing and troubleshooting. ## Future Phases The initial project focuses on reliable document processing and printing. Additional phases may include: * Sage 100 ERP integration * Automatic sales order creation * Inventory verification * Customer acknowledgment emails * Shipping workflow automation * Dashboard and reporting * AI exception handling * Multi-location printing We are looking for a long-term development partner who can continue improving the system over time. ## Required Skills Please apply only if you have strong experience with most of the following: * OpenAI API / ChatGPT API * Gmail API * OCR technologies (Tesseract, Azure Document Intelligence, Google Vision, AWS Textract, or similar) * Intelligent Document Processing (IDP) * PDF parsing * Workflow automation * Python * REST APIs * Windows automation * Network printing * Error handling and logging * AI document classification Experience with the following is a significant advantage: * n8n * Microsoft Power Automate * Make.com * ERP integrations * Sage 100 * Purchase Order processing * Manufacturing or distribution businesses ## Deliverables The completed solution should: * Run continuously with minimal supervision. * Be reliable enough for production use. * Handle errors gracefully. * Be well documented. * Be easy for our staff to maintain. * Be scalable as our order volume grows. ## To Apply Please include: 1. A description of similar automation projects you have completed. 2. Which automation platform you recommend (Python, n8n, Power Automate, Make, or another solution) and why. 3. Examples of AI document processing or OCR projects you've built. 4. Your experience integrating with ERP systems. 5. Your estimated timeline. 6. Your hourly rate or fixed-price proposal. Please begin your proposal with the phrase: **"I have built AI document automation systems."** This helps us identify applicants who have carefully read the project description. We are looking for a long-term partner, not just someone to complete a single project. If this project is successful, additional work will include ERP integration, warehouse automation, customer service automation, purchasing automation, and AI-driven business process improvements.

Description We are a US-based software company that already runs AI coding agents in daily engineering work. We are looking for a senior agentic development expert to help us push further. This is a specialist engagement, not an entry-level or generalist AI role. We want someone who has done this for real teams shipping production code and can go deep quickly. The engagement starts with a focused review of how we use agents today and where they can safely take on more, followed by a practical plan we can act on. Specifics are shared under NDA once we shortlist. You are a strong fit if you: - Have designed and rolled out agentic development workflows for a production engineering team, with results you can point to - Know Claude Code at an expert level: harness setup, context management, custom skills and slash commands, subagents, hooks, and MCP - Have integrated agents into an existing codebase and CI, including automated review and guardrails - Can advise on running agents securely around proprietary code and secrets - Can assess a team's current setup and turn it into concrete, sequenced steps This is probably not the right fit if: - Your experience is mostly personal projects, tutorials, or casual use of AI chat tools - You have used AI coding tools but have not set up team-level workflows or guardrails - You are a generalist looking to branch into AI Nice to have: - Python backend and web application experience - Experience with automated, agent-driven code review and test workflows Engagement: - Remote, expert-level rate - Short initial engagement with potential to extend - Some availability for scheduled, recorded calls - NDA required before we share specifics To apply (proposals without these will not be considered): - A specific example of an agentic development setup you built for a team, what you designed, and the outcome - The AI coding agents you have worked with and the depth of that work - Links to anything that shows your work (skills or agent configs, writeups, repos, demos), if you can share them

About us: Luxe Intelligence is a Baltimore based AI consulting firm. We design and deliver custom AI agent systems for business clients, including regulated industries, with a growing security and government-adjacent practice. We design the system and own the client relationship. You build to spec. The kind of work: Real examples of project types on our roadmap: - Data matching and compliance checking agents that cross-reference large lists (10,000+ rows) with no shared ID, using fuzzy name matching, confidence scoring, and human review flags - Research agents that pull from defined sources and produce structured memos with citations, and say "unverified" instead of guessing - Workflow automations across webhooks, spreadsheets, CRMs, Slack, and email - Read and write-back integrations with systems of record like Salesforce - Deployments inside client cloud environments with audit logging and security review support Must haves: - Strong Python, including pandas and API work - Hands-on experience with LLM APIs (Anthropic, OpenAI): prompt design, structured outputs, cost control - Fuzzy matching or entity resolution experience on real data - Cloud deployment on AWS, Azure, or GCP - Security-minded engineering as a habit, not an afterthought: secrets management, least-privilege access, encryption in transit and at rest, audit trails, human-in-the-loop review steps - Clear written English and documented handoffs Nice to have: - A real cybersecurity background: security engineering, compliance frameworks (SOC 2, NIST, FedRAMP awareness), or secure deployment in regulated environments - US citizenship with eligibility for a government security clearance, or an active clearance, is a plus and worth mentioning - Make.com or similar automation platforms - Salesforce API - Experience answering client security questionnaires How we work: Fixed-price milestones scoped from agreed hour estimates, paid on delivery and approval. NDA signed before any project details are shared. No client contact; all communication runs through Luxe. Some overlap with US Eastern hours. Every engagement starts with one small paid test milestone. Strong performance can grow into a larger ongoing role. To apply, answer these four things, and start your reply with the word CHARCOAL so we know you read this far: 1. Describe a fuzzy matching or entity resolution project you built. How big was the data, and how did you score confidence? 2. Describe an LLM-powered system you deployed into someone else's environment. What broke, and how did you fix it? 3. Estimate this: two lists, about 10,000 rows and 2,000 rows, no shared ID. Need matches, confidence scores, and a monthly flagged-items report. Roughly how many hours, broken down however makes sense to you? 4. Your hourly rate, your weekly available hours, and any security or clearance background.

We're a growing service company looking for an experienced developer to build a Slack bot that answers employee questions about our HR policies, SOPs, and internal documentation. Team members will tag the bot in a channel, ask a question in plain language, and receive a conversational, accurate answer grounded in our documented materials. **This is a build + teach engagement.** I have no coding background, and a core requirement of this project is that you walk me through your decisions and architecture as you build, so I can understand, maintain, and eventually extend the system myself. If you're a strong developer but don't enjoy explaining your work, this isn't the right fit. ## What You'll Build A production-ready Slack bot with the following architecture: - **Slack integration** using Slack's Bolt framework (Python or Node.js — your recommendation welcome) - **Retrieval-Augmented Generation (RAG)** pipeline: questions are matched against our documentation via semantic search, and relevant context is passed to an LLM for a conversational answer - **Vector database** (Pinecone, Weaviate, or a comparable option you can justify) storing embeddings of our policies, SOPs, and transcripts - **OpenAI API** integration for embeddings and chat completions - **Document ingestion pipeline** that can handle multiple source formats: Word docs, PDFs, spreadsheets, and plain-text transcripts (e.g., exported Loom video transcripts) - **Source citations** in bot answers, so users can see which policy or document the answer came from - Deployment to a cloud environment (AWS, Heroku, Railway, or similar) with clear instructions for how it runs and how to restart or update it ## Technical Requirements You should have demonstrable experience with: - Slack app development (Bolt framework, event subscriptions, OAuth/permissions setup) - OpenAI's API (chat completions and embeddings) - RAG architecture and vector databases (Pinecone, Weaviate, Qdrant, pgvector, or similar) - Python or Node.js backend development - Cloud deployment and basic DevOps (environment variables, API key security, uptime) **In your proposal, please link to or describe at least one similar project you've built** — ideally a Slack bot, a RAG system, or an LLM-powered internal tool. ## Deliverables 1. A working Slack bot deployed to production and connected to our Slack workspace 2. Document ingestion process (with instructions or a simple tool for me to add new documents myself as our documentation grows) 3. Full source code in a repository I own, with clear comments 4. **Written documentation** covering: system architecture, how each component connects, how to add/update documents, how to update API keys, and common troubleshooting steps 5. **Teaching sessions**: recorded screen-share walkthroughs (or live calls) at each major milestone explaining what was built and why — I estimate 3–5 sessions of 30–60 minutes 6. A handoff session at the end where we test the bot together and review maintenance procedures ## Communication & Working Style - Regular progress updates (at minimum, 2x per week) - Willingness to explain decisions in plain English, not just technical jargon - Patience with beginner questions — teaching is part of the paid scope, not a favor - Fluent written and spoken English - Availability for scheduled video calls (please note your time zone in your proposal) ## Scope Notes - Initial document set is modest, but the system should be designed to scale as our documentation library grows significantly - Future phases may include: automatic transcript ingestion from Loom, additional Slack channels/workflows, and analytics on what questions get asked — mention if you have experience with any of these - I will provide: Slack workspace admin access, OpenAI API account, and all documentation to be ingested ## How to Apply In your proposal, please include: 1. A brief description of a similar project you've built (links or screenshots appreciated) 2. Your recommended tech stack for this project and a one-paragraph explanation of why 3. Your approach to the teaching/documentation component 4. Estimated timeline and total cost (fixed price preferred; open to milestone-based payment) 5. Your time zone and general availability Proposals that are clearly personalized and address the teaching component will be prioritized. Generic copy-paste proposals will be declined.

I have an archive of approximately 1600 Epson Print CD projects, the majority in EC4 format (approximately 80%), with the remainder in EC3. This is an automation project, not an artwork recreation project. I am looking for an experienced Windows automation/software developer to create a reusable Windows utility that works with the Epson Print CD application. Project Background Epson Print CD saves projects in the proprietary .EC4 format. Epson's current DiscProducer software does not directly import EC4 project files, so I am looking for an automated solution that uses Epson Print CD to generate high-quality PNG exports while preserving the original project layout. The utility should: Automatically open EC4 project files. Render each project using Epson Print CD. Export each project as a high-quality PNG image. Preserve artwork placement, scale, disc alignment, text positioning, and overall image quality. Process multiple files automatically with minimal or no manual intervention. Preserve original filenames where practical. Phase 1 – Paid Proof of Concept The posted budget applies only to this phase. For the proof of concept, I will provide approximately 10–20 representative EC4 files. The attached sample files are provided only to illustrate the variety of artwork and layouts contained in my archive. They are not the complete proof-of-concept dataset. The objective of Phase 1 is to demonstrate that the proposed automation can reliably produce PNG files that preserve the original project layout and print quality. Success Criteria A successful proof of concept should demonstrate that the automation can: Process multiple EC4 files automatically. Produce consistent, high-quality PNG output. Preserve the original artwork layout and print quality. Operate reliably enough to be expanded into a production workflow. If Phase 1 is successful, I intend to negotiate a separate fixed-price agreement (or additional milestones) for: Completion of the production-quality automation utility. Additional refinements, if necessary. Conversion of the remainder of my archive, if mutually agreed. Preferred Experience Experience with one or more of the following is preferred: Windows desktop automation AutoHotkey Python Win32 API GUI automation Windows desktop application development Macro automation Experience with Epson Print CD or similar Windows desktop applications is helpful but not required. When Responding Please include: A brief description of similar Windows automation projects you've completed. Your proposed approach for automating this workflow. Any questions you have before beginning. I am looking to establish a long-term working relationship with the right developer if the proof of concept is successful. I welcome alternative technical approaches if you believe there is a more effective solution than the one described above.