We run a digital marketing agency serving audiology and hearing care practices. We have an existing integration between Counsel Ear (our clients' EMR system) and GoHighLevel via Make.com webhooks. The automation is designed to push updated patient information from the EMR into GHL in real time. The scenario is already built, but recent changes introduced data mapping errors and broken field syncing that weren't there before. We need someone who can quickly diagnose what went wrong, clean it up, and make sure the webhook is passing data correctly end-to-end. What you'll do Review the existing Make.com scenario and identify exactly where the data flow is breaking or mapping incorrectly Rewrite or reconnect the webhook in Make.com so that CounselEar patient data maps correctly into the appropriate GHL contact fields Test the integration thoroughly with live or sample data to confirm everything syncs reliably Document what you built clearly enough that our team can understand and maintain it going forward Requirements Solid, hands-on GoHighLevel experience — you know how custom fields, contact records inside GHL Proven Make.com experience — specifically webhooks, data parsing, field mapping, and error handling in multi-step scenarios Comfort troubleshooting webhook payloads — reading raw JSON, spotting mismatches, and fixing them cleanly Ability to communicate clearly about what was wrong, what you changed, and why — we've already had one experience with someone who introduced new problems, so clear documentation matters Experience with healthcare or EMR integrations is a plus — familiarity with HIPAA-adjacent data handling is helpful, though this role is technical, not compliance-focused Nice to have Any prior experience with CounselEar or similar EMR platforms. If you've connected any healthcare practice management or EMR system to a CRM via webhooks, tell us about it. Scope and budget This is a focused, project-based engagement. The core work is fixing and stabilizing an existing build — not starting from scratch. We expect this to be completable in a few hours for someone who genuinely knows these platforms. We will have occasion need to set up and connect new accounts as they sign up.

I ran a travel agency. We are looking for an experienced AI developer to build an AI-powered travel sales assistant aka ai-agent. The assistant should chat with customers, collect trip requirements, search for relevant tours/packages, answer common travel questions, and send qualified leads to the sales team. Main Features - Understand natural language travel requests - Collect key trip details: destination, dates, budget, number of travelers, preferences, etc. - Search tours/packages through API or structured data - Recommend suitable travel options - Answer questions using our internal knowledge base - Capture and qualify leads - Send qualified leads to Telegram, CRM, or email - Escalate to a human agent when needed Preferred Experience - AI agents / conversational assistants - RAG and vector databases - LangGraph, LangChain, or similar frameworks - Python / FastAPI - API integrations - Lead qualification workflows - Prompt engineering and hallucination control S t a r t your proposal with a w o r d travel. This will tell me you read it. Nice to Have Experience with travel, booking systems, tour operators, or recommendation engines. Deliverables - Working MVP of the AI travel assistant - Travel requirement collection flow - Search/recommendation logic - Knowledge base integration - Lead handoff workflow - Basic documentation and deployment support Please Include 1. Examples of similar AI agents or RAG systems you have built 2. Your recommended architecture 3. Estimated timeline for an MVP 4. Your preferred tech stack 5. How you would prevent hallucinations around pricing, availability, policies, and visa information

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.

Join Congo Cross Solutions, an AI agency dedicated to enhancing management processes through automation services. Our exclusive focus is management consultancy firms. These firms operate with complex workflows and high-value processes. We build systems that radically improve efficiency, reporting, and client operations. We need high-performing "killers" who focus entirely on driving measurable results. You will develop and implement tailored AI automation solutions for our consultancy clients. The ideal candidate will have experience in AI automation and a strong understanding of management systems. Responsibilities include analysing current processes, designing AI-driven solutions, and collaborating with our team to integrate these solutions effectively.

We are looking for a Microsoft 365 document workflow consultant to help us design and test a practical process for turning raw proposal notes into a formal, styled Microsoft Word document. We operate in Microsoft 365 Copilot. We are looking for someone who has experience solving document workflow problems involving Word templates, structured input, formatted sections, styled text, tables, bullet lists, numbered lists, headers, footers, and editable Word output. The business goal is to keep the project manager or proposal lead focused on drafting the content for each section, without getting caught up in Word templates, formatting, styles, layout, or document production issues. Ideally, one team member can provide section-by-section notes or draft language, and another team member responsible for document production can use a streamlined or automated process to turn those raw notes into a polished, formal Word document. The first deliverable should be a small proof of concept, along with an explanation of the workflow and how it could be maintained by a non-developer business user.

I need an ai agent i to combine offer letters, acceptance, onboarding new staff by sending out specific emails to different team members for different positions, setting up emails automatically in Microsoft360, automatically onboarding on quickbooks for payroll and sending out policy and procedures. It should be done in N8N utilizing my server this is my chat prompt, but I would like you to also add to the project idea. You are my HR & Onboarding Operations AI Agent for ProCare. Your job is to manage the full employee onboarding workflow from offer letter through payroll setup, Microsoft 365 account creation, policy distribution, internal notifications, and first-day readiness. You must operate like a professional HR operations manager. Accuracy, compliance, privacy, and sequencing are critical. Core workflow: 1. Collect or confirm candidate details: - Full legal name - Personal email - Phone number - Position/title - Location - Department - Manager/supervisor - Start date - Employment type: W-2, 1099, full-time, part-time, PRN - Pay rate/salary - Commission/bonus terms, if any - Work schedule - Required licenses/certifications - Required systems/access 2. Generate and send offer letter: - Use the correct company template - Include title, start date, pay, schedule, reporting manager, at-will language, contingencies, and signature block - Send to candidate for signature/acceptance - Save final accepted copy in the correct employee file 3. After acceptance: - Send welcome email to candidate - Send onboarding checklist - Send policy/procedure packet - Send required forms: W-4, I-9, direct deposit, emergency contact, handbook acknowledgment, confidentiality/HIPAA acknowledgment, job-specific documents 4. Notify internal team members: - HR/admin: create employee file and track documents - Manager: prepare schedule and first-day plan - IT: create Microsoft 365 email, Teams, SharePoint, system access - Payroll/bookkeeper: add employee to QuickBooks Payroll - Compliance: verify license, background check, HIPAA training, role-specific credentialing - Operations: add to org chart, phone list, scheduling system, uniforms/badge if applicable 5. Microsoft 365 setup: - Create email address using company naming convention - Assign correct license - Add to appropriate groups, Teams, shared mailboxes, calendars, and SharePoint folders - Send credentials securely according to company policy - Confirm setup completion 6. QuickBooks Payroll onboarding: - Add employee/contractor profile - Enter pay rate, pay schedule, tax status, direct deposit status, start date, work location, and department/class - Do not finalize payroll setup until required tax and direct deposit forms are complete 7. Compliance safeguards: - Never send Social Security numbers, banking information, DOB, medical information, or sensitive HR documents by normal email unless secure transmission is available - Do not create payroll records or accounts if required information is missing - Ask for missing information before proceeding - Keep an audit trail of every step completed - Confirm before sending any external email or making permanent system changes unless I have specifically approved auto-send mode 8. Document organization: Create or update an employee onboarding folder with: - Offer letter - Signed acceptance - Payroll forms - Compliance forms - Licenses/certifications - Policy acknowledgments - Training checklist - Internal onboarding checklist 9. Communication style: - Professional - Clear - Warm - Brief - No legal overpromising - No casual language in official HR documents 10. Output format every time: - Candidate summary - Missing information - Documents to generate - Emails to send - System actions to complete - Internal notifications - Compliance risks - Recommended next step Before taking action, always show me a checklist and ask for approval unless I say: “Execute onboarding.”

We're looking for a production software engineer who builds agentic systems — and ships them into live, revenue-bearing environments. What you'll build: The agentic framework that orchestrates decisions across the lead funnel — tool use, multi-step workflows, and the logic that ties them together into a reliable system. The integration layer that wires our decision and pricing models into a live production pipeline, so the optimization logic actually runs against real traffic. The reliability layer that production demands: latency management, error handling, retries and fallbacks, observability, and graceful degradation when something upstream fails. Evaluation and testing for non-deterministic systems — how you verify an agentic workflow behaves correctly when the same input doesn't always produce the same output, and how you catch regressions before they hit revenue. The deployment and monitoring setup that lets us ship changes safely and see what the system is doing in production at all times. What we're looking for: Must-haves: 5+ years total software engineering, with 2+ years specifically building LLM/agentic systems. Strong production software engineering — you've built, shipped, and operated real systems that something important depended on. Built LLM-powered agents or agentic workflows in production, not just prototypes or demos Hands-on with modern agent frameworks (LangGraph, AutoGen, CrewAI, Letta, or similar) Experience with orchestration, tool use, and evaluating/testing non-deterministic systems Strong Python (TypeScript a plus) Solid instincts for reliability: observability, error handling, latency, and failure modes Strong signals: Founding or staff engineer experience at an AI/agent company (think Cognition, Adept, Imbue, Reflection, Lindy, Decagon, Sierra, Cresta, or similar) Open-source contributions to agent frameworks (Cline, LangGraph, AutoGen, CrewAI, Letta) Experience integrating ML models into live production systems Not what we're after: No-code / automation-only builders (Zapier, Make) and GPT-wrapper work Prompt engineering as the primary skill Demo-only agent experience with nothing shipped to production

AI Automation Specialist / Workflow Automation Assistant We are looking for a skilled AI Automation Specialist who can help our business automate repetitive tasks, improve workflows, and integrate AI tools into our daily operations. The ideal candidate must be knowledgeable in using tools such as ChatGPT, Claude, Manus AI, and other AI or automation platforms. We need someone who can understand our business processes, suggest practical automation solutions, and implement systems that save time and reduce manual work. This role is ideal for someone who is proactive, tech-savvy, detail-oriented, and experienced in using AI tools for business productivity. Responsibilities •The hired specialist will help with setting up and improving AI-assisted workflows, including but not limited to: •Creating automated workflows using AI tools such as ChatGPT, Claude, Manus AI, and similar platforms. •Building prompts, templates, and AI agents for repetitive business tasks. •Automating research, document drafting, email workflows, data organization, lead generation, reporting, and task management. •Creating standard operating procedures for AI-assisted processes. •Testing and improving automation workflows to make sure outputs are accurate and useful. •Recommending AI tools and systems that can improve productivity. •Helping the team use AI tools properly through simple guides or training materials. •Integrating AI tools with platforms such as Google Workspace, Notion, Airtable, Zapier, Make, Slack, Trello, ClickUp, or similar tools, if needed. Required Skills •The applicant should have experience with: •ChatGPT, Claude, Manus AI, or similar AI platforms. •Prompt engineering and AI workflow design. •Business process automation. •No-code or low-code automation tools such as Zapier, Make, Airtable, Notion, Google Sheets, or similar platforms. •Research, content generation, document automation, and data processing using AI. •Creating clear documentation and workflow instructions. •Problem-solving and process improvement. Preferred Qualifications •Experience working with service-based businesses, agencies, law firms, consulting firms, or administrative teams is a plus. •Experience creating AI agents, custom GPTs, automation templates, or internal productivity systems is preferred. •Strong communication skills and the ability to explain technical processes in simple terms. •Ability to work independently and suggest improvements without being micromanaged. Sample Tasks •Create AI prompts for drafting emails, proposals, reports, and client communications. •Set up workflows for automatically organizing leads, inquiries, documents, or tasks. •Use ChatGPT or Claude to summarize long documents and generate action items. •Create AI-assisted systems for research, content planning, or admin work. •Build templates that our team can reuse for daily operations. Who We Are Looking For We are looking for someone who is not just familiar with AI tools, but someone who can think strategically about how AI can make our work faster, cleaner, and more efficient. You should be able to review a manual process and say: “This can be automated, and here’s the best way to do it.” To Apply •Please include the following in your application: •Your experience with ChatGPT, Claude, Manus AI, and automation tools. •Examples of AI workflows or automations you have built. •The tools you are most comfortable using. •Your hourly rate or project-based rate. •A short explanation of how you would help automate business operations for a small team.

We're a financial services firm (SBA loan brokerage) processing a high volume of loan and financial documents every week, bank statements, applications, and deal files, most of it handled manually. We're looking for an experienced AI engineer to build a document-automation and AI agent system to take this off our plate. What we need: An AI pipeline that extracts and structures data from PDFs and bank statements (OCR + LLM) and pushes it into our spreadsheets/CRM automatically A RAG-based system so our team can ask questions across our documents and get source-cited answers An AI agent that scores and prioritizes incoming deals against our historical data, flagging the ones most likely to close Workflow automation to connect everything (n8n / API integrations) You should have strong experience with: RAG (Retrieval-Augmented Generation) and LLM applications AI agents and tool-calling workflows Document extraction, OCR, and structured outputs Python, LangChain/LangGraph, and vector databases Workflow automation (n8n, APIs) Accuracy is critical for us — we need a system that grounds its answers in our data and doesn't hallucinate numbers. This is an ongoing project with room to grow. Please share examples of document-AI or RAG systems you've built.

I’m looking for someone who can help me design and build a scalable system for video ad creative production using AI. This is not a video editing role. This is not a basic marketing role. This is for someone who understands how to combine AI + workflows + creative production to build a system that can: * Generate ideas (angles, hooks, concepts) * Turn those into scripts * Produce video creatives (AI, UGC-style, or hybrid) * Iterate and improve based on performance ⸻ The Goal: Build a repeatable, scalable creative engine that allows my team to: * Produce high-quality video ads faster * Test more angles and hooks * Iterate on winning creatives * Scale across multiple clients and campaigns This needs to be realistic and usable, not theoretical. ⸻ What I’m Looking For: Someone who can: * Design the full workflow from idea → script → video → iteration * Recommend the best tech stack to make this actually work at scale * Help implement and structure the system so a team can use it daily * Balance automation with quality (avoid generic AI output) ⸻ Important: I do not want someone who just lists tools. I want someone who understands: * What parts should be automated * What parts should stay manual * How to maintain creative quality at scale ⸻ Ideal Candidate: * Has built or worked on AI-driven creative systems * Experience with video ad production for paid traffic * Understands direct response marketing and what converts * Thinks in systems, workflows, and scale * Can simplify complexity into something usable ⸻ How to Apply: Please include: 1. Have you built anything like this before? If yes, explain what you built and the results. 2. What tech stack would you recommend for this and why? (Be specific and practical.) 3. How would you structure the workflow from idea → finished video ad? 4. (Optional but preferred) Examples of video ads or systems you’ve worked on. ⸻ Goal: Create a system that doesn’t just “make videos” — it consistently produces better-performing ad creatives at scale. ⸻ If this works, this can turn into ongoing work building and optimizing the system.