Hi, we have an existing business that uses expert reviewers to review college applications (common app, transcripts, test scores, essays) and write a freeform critique. We have 944 applications and 1,035 reviews in a Mysql database. We are working on bringing in another 719 aplications and 1,593 critiques. What is in an application is public domain, and our critiques are a minimum of 300 words. We intend to use RAG technology to create an AI version of the business that can create critiques for new applications. We need a data scientist to spend a couple of weeks to: - Review our data - Quantitatively assess our data and the feasibility that it can generate a RAG based solution that works (similar to old fashioned sample analysis in regular statistics) - Give us an assessment of the viability of creating AI critique outputs - Possibly suggest suplemental or alternative methods to RAG systems This is not a development or build - it is an analysis phase. If the math shows this is a viable track, we could also contract for the development phase. Let us know what you think about this in terms of: - have you done this before? - how many hours would it take you to do this? - could you take on the development in a later stage as well? Cheers, BKW

I need someone who can help me build out an internal AI workflow that collects hundreds of large PDFs, extracts dozens of data points from the PDFs, and stores them in a database. The workflow should be able to handle large volumes of data efficiently and accurately. Experience with AI and data processing is essential.

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.

1. Full Optimization of the Mac • Tune the entire system for AI performance on Apple Silicon (MLX, Neural Accelerators, unified memory, power/thermal settings, permissions, clean environment) • Make everything stable, fast, and easy for a non-technical user 2. Easiest Possible App-Building Environment for a Non-Coder Install, configure, and thoroughly set up the current best tools that let a complete beginner build a real construction app by describing what they want in plain English (or simple clicks): • Claude-powered building tools (Claude Projects, Artifacts, Skills, Claude Code in guided/non-coder mode, desktop features, etc.) • Top AI no-code / low-code / AI-app-builder platforms that work great on Mac in 2026 (examples of the type I mean: modern equivalents of Lovable, v0, Replit Agent, Bubble with AI, Glide, Softr, FlutterFlow AI, or whatever is currently the absolute easiest and most powerful for non-coders) • Local AI helpers that assist with building without requiring code knowledge • Clear templates or starting points relevant to construction/project management/estimating apps • Simple step-by-step workflows so I can go from “I want an app that does X” to a working app with minimal frustration The goal is that I can build and improve my construction app myself after you finish, without ever writing traditional code. 3. Ready-to-Use AI Agents for My Construction Business Create and configure practical agents I can use immediately (and that will also help while I build the app): • Email file intake agent: watches email or a folder, pulls in project files, organizes them, and prepares them for takeoff • Masonry takeoff agent: handles large blueprint/PDF sets for wall runs, openings, brick/CMU counts, mortar, grout, rebar, lintels, etc. (integrate or set up the strongest current specialized tools + Claude/local vision pipelines) • Estimating, quoting, and proposal agents • Document and contract review agents • Simple business agents (client follow-ups, notes, photo tools, etc.) Everything should be simple to run, with clear buttons, prompts, or chat interfaces — no coding required to use them. 4. Supporting Setup • Secure and simple way to manage any API keys • File organization system for projects and plans • Privacy-focused options (local models where useful) • Recommendations for the best current AI construction/estimating tools that a non-coder can actually use 5. Training & Handoff (Critical) • Simple written guides written for a complete beginner • Short, clear screen-recorded videos showing exactly how to use every tool and agent • Live training sessions where you walk me through building a small example and running a takeoff • Ongoing tips so I can keep using and improving everything myself Required Skills • Expert at setting up AI tools and agents on Apple Silicon Macs (MLX, Ollama, LM Studio, Claude ecosystem) • Strong experience with the latest no-code / low-code / AI app builders that non-coders can actually succeed with • Ability to create simple, reliable agents for document/PDF processing and construction-style workflows • Excellent at explaining technical setups to complete beginners • Construction or estimating experience is a big plus Deliverables 1. Fully optimized and cleaned-up MacBook Pro 2. Complete, beginner-friendly AI app-building environment installed and configured 3. Working set of construction AI agents (email → takeoff → estimating, etc.) ready to use 4. Clear beginner documentation + short video guides 5. Live training so I can confidently build my app and run takeoffs myself To Apply Please include: • Experience helping non-coders use AI tools to build real applications • Experience with Claude, local Mac AI setups, and current no-code/AI builders • Any construction, estimating, or document-processing agent work • A short description of how you would make app-building as easy as possible for someone who cannot code • Timeline and cost estimate I am ready to start immediately. I want a complete, well-documented setup that turns this powerful new Mac into a system a non-technical masonry contractor can actually use to build his own app and automate takeoffs and business work. Thank you.​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​

EroFlow Intelligence is an enterprise-grade, autonomous AI orchestration pipeline designed to mitigate global supply chain disruptions for aerospace manufacturing. Built using a multi-agent framework, the system automates the entire lifecycle of risk detection, impact analysis, and procurement mitigation without requiring human intervention for standard operational anomalies. The architecture coordinates three specialized, asynchronous AI agents that communicate via a centralized event bus to solve complex logistical bottlenecks in real-time. Core Agent Architecture & Workflow 1. The Sentinel Agent (Data Ingestion & Extraction) Role: Continuous Global Monitoring. Function: Utilizes advanced LLM-driven web scraping and unstructured data extraction to monitor global news feeds, geopolitical shifts, weather anomalies, and shipping port telemetry. Trigger: If it detects a disruption (e.g., a port strike or critical mineral shortage), it extracts key entities (materials affected, estimated delay times) and passes a structured JSON payload to the orchestration layer. 2. The Impact Assessment Agent (Predictive Modeling) Role: Deep Cross-Referencing & Analytics. Function: Upon receiving a trigger, this agent cross-references the disrupted material with the company’s internal ERP (Enterprise Resource Planning) database and current inventory levels. Output: It runs a predictive analysis to determine exactly which production lines will stall and calculates the financial risk, assigning a high/medium/low priority score to the event. 3. The Mitigation & Logistics Agent (Autonomous Execution) Role: Operational Resolution. Function: If the risk score exceeds a specific threshold, this agent is authorized to take action. It autonomously queries pre-vetted alternative suppliers via APIs, negotiates standard volume pricing based on historical contract data, drafts a comprehensive procurement proposal, and queues the purchase order for final human sign-off (or executes it automatically if under a certain dollar cap). Technical Stack (The Blueprint) Frameworks: LangGraph / CrewAI (for multi-agent state management and deterministic routing). Core Language: Python 3.11+ Data Layer: PostgreSQL (for ERP syncing) & Pinecone / Qdrant (Vector database for storing and querying supplier contract PDFs and historical compliance documentation). LLM Orchestration: OpenAI GPT-4o / Anthropic Claude 3.5 Sonnet utilized via structured outputs (Pydantic parsing) to ensure strict API data integrity. Hosting & DevOps: Containerized via Docker, orchestrated via Kubernetes, and deployed on AWS with asynchronous task queues managed by Celery and Redis. Quantifiable Business Results (The Hook) 92% Reduction in supply chain anomaly response time (from 48 hours down to 14 minutes). Automated Recovery: Successfully mitigated over 140 potential production line stalls autonomously in simulated stress tests. Cost Efficiency: Saved an estimated $1.2M in expedited shipping fees by predicting bottlenecks 10 days before they impacted manufacturing floors.

We are seeking an AI Consulting Developer to enhance our AI Consulting services. The ideal candidate will have experience in AI Consulting and be able to develop innovative solutions. Responsibilities include analyzing business needs, designing AI systems, and implementing AI solutions. The candidate should be able to work independently and collaboratively as part of a team.

We are looking for someone with AI experience and Quick book experience to automate our order processing steps that involves mix flavor cases and multiple delivery destinations. Automate the order entry into Quick books enterprise. Generation of total weight, pallet fit for each destination. Please share examples of your past work.

• Proven experience building with the Anthropic/Claude API (or comparable LLM APIs) in production settings • Experience with document/presentation generation workflows (PowerPoint, Google Slides, or similar) • Strong understanding of prompt engineering and structuring AI agents for repeatable business tasks • Ability to translate a non-technical team’s operational pain points into a working technical solution • Clear communicator, comfortable scoping ambiguous requirements into a phased build To apply, please share: • Relevant past projects (especially any AI agent/automation builds) • Your general approach to a project like this Ideally this is an Ai expert who has worked with Interior Design firms that use Claude and other possible Interior Design Ai programs to increase deliverables and productivity of team members and efficiencies.

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 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.