Looking for an experienced AI developer to help build an AI agent using Claude. Requirements: Experience building AI agents and autonomous workflows Strong experience with Claude and Anthropic models Ability to integrate external data sources and APIs Experience deploying production-ready AI solutions Please include: Examples of similar AI agent projects you've built Your experience with Claude Your recommended tech stack Estimated timeline and cost Looking to start immediately.

Forum Intelligence: Project Brief & Initial Rollout 1. Executive Summary & Objective Forum Intelligence is a beginning as a localized data retrieval, processing, and archiving system designed to scrape public municipal records and state legislative data for public oversight. The immediate objective is to build a functional, highly resilient prototype focused on the Tri-Cities region (Burbank, Glendale, and Pasadena, California). The system will autonomously ingest messy, unstructured municipal data (City Council meeting minutes, agendas, public notices, and legislative PDF text, recorded mp4), clean it, and make it fully searchable and queryable via a localized AI agentic framework. 2. Phase 1 Scope: The Tri-Cities Rollout Th engineer will be responsible for building two primary pillars: A. Resilient Scraper Bots • Target Ingestion: Monitor and pull data from Burbank, Glendale, and Pasadena municipal portals and California legislative feeds. • Data Types: Brittle HTML sites, heavily nested tables, public notices, legislative drafts, and massive unstructured PDF archives. • Requirements: The scraping architecture must be exceptionally robust, utilizing intelligent error handling, retry semantics, and pagination tracking to handle frequent municipal website layout changes without breaking the pipeline. B. Ingestion & Vector Pipeline • Parsing: Extracting clean text from poorly formatted documents and scanned PDFs. • Local RAG (Retrieval-Augmented Generation): Chunking and embedding the data locally into a vector database (e.g., pgvector, Chroma, or Milvus) to enable semantically accurate entity linking and contextual search. 3. Targeted Hardware Stack To ensure maximum data security, strict public oversight integrity, and predictable operational costs, Forum Intelligence is skipping commercial cloud APIs in favor of an on-premise, localized NVIDIA enterprise deployment. The production roadmap aligns precisely with the new computing patterns detailed in NVIDIA’s latest hardware roadmap: • Inference & Token Generation: Running local open-weight frontier models (e.g., Neotron 3 Ultra or Claude/Llama equivalents) optimized for reasoning and long-context tool use. • Compute & Orchestration: The backend infrastructure is architected around NVIDIA’s dedicated agentic architecture, utilizing high-instructions-per-clock (IPC) Vera CPUs paired with Vera Rubin GPUs. • Memory & Storage Processing: Utilizing NVIDIA’s unified memory fabric and data processing units (DPUs) for ultra-low latency context management, KV caching, and fast vector database retrieval. 4. Immediate Milestones for the Engineer 1. Architecture Design: Map out the database schema and local inference ingestion loop. 2. Tri-Cities Scraper Deployment: Write and deploy the initial automated bots for Burbank, Glendale, and Pasadena. 3. Local MVP Pipeline: Demonstrate a local RAG pipeline where a user can query the Tri-Cities scraped records and receive grounded answers with exact source attributions. The above was AI generated from months long conversations with Gemini. The goal is to prove the concept then roll out to LA County, state of CA, and then the country.

ABOUT THE PROJECTS. I run a curated marketplace on Shopify (The Ever Good) and I am building out an AI automation system to handle routine tasks in the business. I am AI-savvy and have built a Python agent myself, so I understand what I am asking for. I have the architecture planned and the business requirements semi-documented for each piece. I simply do not have the time to build everything I want to build, which is why I need a developer to work alongside me. The first project is a product review collection and import system. If it goes well, there is ongoing work building out additional agents over time, one at a time. This is a potential long-term engagement depending on how the first project goes. WHAT WE ARE BUILDING. The overall system is a set of AI agents that handle specific business tasks and route outputs to a simple dashboard where I can review, approve, and trigger actions before anything goes live. The dashboard is a Lovable build that gives me a single place to monitor agent status, review outputs, and approve or return anything that needs a human decision before it moves forward. Agents are planned across several areas of the business. We will build one at a time. I will walk you through the requirements for each before you start. Examples of agents here by business category (these could change): - MARKETPLACE & CATALOG. Product Reviews (first project), Catalog Enrichment and SEO, Pricing and Margin Monitor, New Product Auto-Pricer, Maker Stories, Maker Audit, Maker Analytics, Review Monitor. - CONTENT & SOCIAL. Content Generation, Cultural Moment Monitor, Social Publishing, Pinterest Curator, Instagram DM Automation, Image Production, Founder Content Amplifier. - MARKETING & ADS. Email Sequences, Paid Media Director, Ads Performance Monitor, LinkedIn Outreach. - SEO and Search. SEO and AI Search Visibility, Crawl Error and Redirects. - THE SCHOOL (Our Coaching Offerings). AI Readiness Assessment, Coaching Prep Tool, Workshop Launcher, Course Completion Monitor, Immersion Round Tracker. - FINANCE & OPS. Profit Police, Cash Flow Forecaster, Financial Health Monitor, System Health Monitor. - CUSTOMER SERVICE & GIFTING. Customer Service Drafts, Gift Inquiry and Proposals, Basket Assembler. OUR TECH STACK (Could Change). - AI AGENT BUILDING STACK. Claude Code, Claude API, Python, Make.com, Replit, Lovable, Google Sheets API, Baserow. - OTHER BUSINESS SYSTEMS. Shopify API, DropCommerce API, Matrixify, Typeform, Stripe API, Yotpo API, Klaviyo API, Instagram Business API, Later API, Pinterest API, ManyChat API, Bannerbear API, LinkedIn API, Google Analytics 4 API, Google Search Console API, DataForSEO API, QuickBooks Online API, Google Drive API. HOW WE WORK. - HOURLY. Collaborative and iterative engagement. - REQUIREMENTS. We review together before each build and refine as we go. - QA. I handle testing and QA on my end. - DOCUMENTATION. All work is documented throughout with decision logs and handoff notes so full ownership and control remains with me at every stage. - IP. All intellectual property and work product belongs to me entirely. - CLAUDE. You are expected to maintain your own Claude environment at a level that supports serious development work with no usage limitations. - ACCESS. All business systems and APIs provided with scoped credentials as needed. - DEPLOYMENT. Production deployment is handled collaboratively. - COMMITMENT. Looking for someone who can help maintain and evolve these tools over time while I retain full control and understanding of everything we build. WHAT I AM LOOKING FOR. - CLAUDE. Must use Claude as your central AI LLM. Experience. Working experience with the Claude API and the tools in the building stack above, or a demonstrated ability to learn new tools quickly. - COMMUNICATION.Clear communicator who works independently and does not need to be managed through a task, but is promptly responsive to me. - MINDSET. Building with AI tools as a regular part of your work. TO APPLY. Please share a brief description of one or two AI agents you have built, what they did, and what tools you used. Include a note on your familiarity with the tools listed above and your hourly rate.

We are seeking an AI Automation Implementation Expert to enhance our business processes. The ideal candidate will have experience in implementing AI solutions to improve efficiency and productivity. Responsibilities include analyzing current systems, identifying areas for automation, and implementing AI-driven solutions. The candidate should be able to work independently and provide insights on AI best practices.

I am looking for a developer or agency to build a web platform called First Responder Academy. The goal is to create the most comprehensive AI-powered training platform for firefighters, EMTs, and paramedics. The platform will initially focus on: 1. Firefighter Oral Board Preparation 2. EMT NREMT Preparation 3. Paramedic NREMT Preparation 4. Firefighter I Certification Preparation 5. Firefighter II Certification Preparation Core Features Required: * User accounts and login system * Membership and subscription management * AI-powered training simulator * Progress tracking * User dashboard * Mobile-friendly design * Modern, professional interface * Ability to scale over time AI Training Features: The AI should be able to: * Conduct firefighter oral board interviews * Score responses * Provide detailed feedback * Generate EMT and paramedic scenarios * Generate Firefighter I and II questions * Create multiple-choice exams * Provide remediation and study recommendations * Increase or decrease difficulty based on performance Knowledge Base Features: The system should allow: * Uploading NREMT skill sheets * Uploading EMS protocols * Uploading Firefighter I and II standards * Uploading department-specific hiring packets * Uploading study guides and training documents The AI should reference uploaded materials when generating questions and grading answers. EMS Features: * EMT training mode * Paramedic training mode * NREMT-style testing * Practical scenario evaluations * Protocol-based learning * Trauma and medical assessment training * Airway management training * Cardiology training Cardiology Module: A major future feature will be ECG interpretation. Requirements: * ECG image library * Random ECG presentation * Student interpretation * AI grading and feedback * Rhythm recognition training * Treatment decision evaluation Firefighter Features: * Firefighter Oral Board Simulator * Firefighter I Exam Preparation * Firefighter II Exam Preparation * NFPA / IFSAC-based content * Scenario-based learning * Multiple-choice testing * Leadership and decision-making exercises Department-Specific Training: The platform should eventually allow users to: * Upload local EMS protocols * Upload department hiring packets * Upload mission statements and values * Receive customized training based on those documents Progress Tracking: The platform should track: * User scores * Weak areas * Practice history * Completion rates * Recommended study topics * Improvement over time Admin Features: * Upload and manage training content * Upload and manage protocol documents * Upload and manage ECG images * Create and edit question banks * View user analytics * Manage subscriptions Technology Preferences: * Modern scalable architecture * AI integration using OpenAI API * Secure user authentication * Cloud-hosted * Responsive design * Easy content management Design Style: * Professional * Modern * Clean * Fire and EMS themed * Dark mode preferred * Red, black, gray, and white color palette Important: I am looking to build an MVP first, not every feature immediately. Phase 1 priorities: 1. User accounts 2. AI training simulator 3. Oral board preparation 4. EMT preparation 5. Paramedic preparation 6. Firefighter I and II preparation 7. Progress tracking 8. Membership system Future phases can include ECG image testing, advanced protocol integration, department-specific customization, and additional first responder training programs. Please provide: * Estimated timeline * Estimated cost * Recommended technology stack * Examples of similar projects * Suggestions for MVP development

**ChatGPT Business + Google Workspace Integration Consultant** I'm looking for an expert to help set up ChatGPT Business as the central AI platform for my medical practice. I need assistance with: * Fixing/migrating my ChatGPT Business workspace * Connecting Gmail, Google Calendar, Google Drive, and Google Docs * Integrating Basecamp * Organizing Google Drive and workflows * Training me on best practices * Building AI workflows for meeting summaries, task management, and office operations This is an initial 3–8 hour project with the opportunity for an ongoing consulting relationship. **Requirements:** * Experience with ChatGPT Business * Google Workspace expertise * Basecamp experience (preferred) * AI workflow automation (Zapier, Make, n8n, etc.) * Excellent communication skills Please include: * Similar projects you've completed * Your hourly rate * Your availability * Why you're a good fit for this project

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 am working on a system using AI to review and respond on Google Drive (Shared Drive) folders of PDF's. Using Gemini as a POC I get responses that sometimes reach outside of my specified folders of content, but sometimes, some PDF files are ignored too. Also, when the response to a prompt come back, the sources are linked. However, the links only bring up the first page of the PDF file wherein the linked source material is, AND NOT THE pdf PAGE of the specific info. I need to have the AI (Gemini, Grok, etc.,) be used to query just.... but all, of the PDF files, within a set of folders in Google Drive (Shared Drive), and to respond with linked content. Said links must open to the PDF PAGE, not just the PDF which houses the specific info. In short, I think I need a viewer, but someone who has experience working with AI and PDF's will likely know the issue I am running into. In the end my system will have a UI attached, so there is a lot of possible side work on this project. First I need to build a better POC. For instance, if I open ONE of the PDF files in Google Drive, I can prompt on that file, and the correct PDF page does come up in the viewer, (While no other files are considered for the queried content.) But when I give Gemini many source PDF's or a folder of PDF's, the links only go to the first page pf the PDF with the information used as the sourcwe.

Project Title: Build Fast Web-Based AI Anime Companion MVP (RAG + Merch Gen) – 15–30 Days, $25K Budget: $18,000–$25,000 fixed Timeline: 15–30 days (3 weeks preferred) Must-Have Skills: FlowiseAI (or LangChain/LlamaIndex), RAG pipelines, OpenAI/Claude/Grok, anime image generation (Leonardo.ai/Ideogram/PixAI), Vercel or Railway deployment Project Goal Build a mobile-friendly web AI Companion for Big A Anime that converts passive FAST viewers into active fans. The key objective is to connect our Pluto TV channel experience directly to the AI companion, allowing viewers to scan QR codes during live programming and instantly access interactive content, recommendations, and merch tied to what’s currently airing—no downloads required. Core MVP Features Web Chat Interface Clean anime-branded chat UI with voice input Mobile-first, responsive Custom domain (e.g., companion.biganime.tv) RAG Knowledge Base Ingest episodes, schedules, transcripts, and metadata Provide accurate recaps, lore, and “what’s on now/next” tied to Pluto TV programming Session memory + light user profiles AI Merch Generator Anime-style image generation (“me as [character]”) Leonardo.ai or similar integration Export + links to Printful/Printify FAST / TV Integration Tools Dynamic QR codes for on-screen use Deep linking between Pluto TV programming and companion experience Voice-friendly prompts (“Ask Big A Companion…”) Admin & Analytics Simple CMS for content uploads Dashboard: usage, queries, merch clicks Technical Requirements Global hosting (CDN) FlowiseAI preferred Full source + documentation 30 days post-launch support Out of Scope Native apps, payments, deep integrations, multi-language Deliverables Live URL, admin access, training, source code, 30-day support Application Fixed bid + 3-week plan 2–3 relevant project links Willingness for small paid test ($500–$800)

We are seeking a skilled freelancer to develop an AI-driven sales pipeline and lead generation system. The ideal candidate will have experience in AI technologies and a strong understanding of sales processes. Responsibilities include designing and implementing AI solutions to enhance lead generation and sales conversion rates. The project requires an intermediate level of proficiency and is expected to last 1 to 3 months.