Mobile app for continuous searching. Enter a query in the search box powered by AI to sharpen up the requst, chose the duration of the search using pop up calendars. Hit submit, the app will continuously search for new information starting ONLY from the start date to the end date. When a new query is found, the app notifies and displays the web link to be clicked on and reviewed. Once the link has been viewed, the link goes from green to red to represent the link has been view and the customer now can delete that notification. The notification includes a time date stamp when the notification was found. Possibly to use AI in the search box to articulate the request being searched. This is a continuous notification app. The customer will have up to 10 queries and 10 notifications per query. The app has to be compatible for Android and IOS. As far as security, there is no information to steal, the customer only needs to creat a login and password, no personal information collected no billing. Billing is handled by the Playstore and Apple store. The app will be subscription based based on the frequency of the search. Ex: search frequency every hour, or search frequency every 5 minutes.

The Client seeks an experienced AI development team to design and build a secure web-based document intelligence platform capable of analyzing multiple related documents, extracting key information, identifying inconsistencies, and generating issue reports. The platform will support complex document sets where information must remain consistent across multiple files and versions. The initial scope focuses on document ingestion, data extraction, cross-document analysis, issue identification, and reporting. Business Objective Develop a scalable SaaS application that enables users to: • Upload and organize multiple related documents • Extract key terms, dates, parties, financial values, and references • Compare information across documents • Identify inconsistencies and missing information • Generate issue reports and review summaries • Maintain document version history • Provide an intuitive dashboard for issue management Phase 1 – Document Ingestion and Processing Requirements Develop a secure document upload module supporting: • PDF • Microsoft Word (.docx) • Microsoft Excel (.xlsx) • Text files System shall: • Extract text from uploaded files • Preserve document structure • Capture headings and section hierarchy • Process tables and schedules • Index document content for search and retrieval Phase 2 – Data Extraction Engine The platform shall automatically identify and extract: • Defined terms • Parties and entities • Dates • Numerical values • References to exhibits and schedules • Section references • Key metadata Extracted information shall be stored in a searchable database. Phase 3 – Cross-Document Consistency Review The platform shall compare extracted information across multiple documents and identify: • Inconsistent terminology • Conflicting dates • Conflicting numerical values • Missing references • Undefined terms • Duplicate provisions • Broken cross-references Examples include: • Same entity referenced using multiple names • Different numerical values for the same item • References to sections that do not exist • Missing exhibits or attachments Phase 4 – AI Review and Issue Identification The platform shall integrate a Large Language Model (LLM) to perform contextual analysis. The AI engine shall: • Summarize document contents • Identify potential drafting inconsistencies • Highlight missing information • Generate issue descriptions • Assign issue severity levels • Provide suggested corrective actions Phase 5 – Dashboard and Reporting Develop a web-based dashboard including: Transaction Workspace • Document list • Upload history • Processing status • Review status Issue Tracker • Issue category • Issue severity • Source document • Description • Resolution status Search Functionality Search by: • Term • Date • Party • Numerical value • Document name Reporting Generate downloadable reports in PDF and Excel format. Technical Requirements Frontend • React or Next.js Backend • Python • FastAPI preferred Database • PostgreSQL Vector Database • Pinecone, Weaviate, or Chroma AI Integration • OpenAI API • Anthropic API • Retrieval-Augmented Generation (RAG) architecture preferred Security Requirements • User authentication • Role-based permissions • Encrypted document storage • Audit logging • Secure API access Deliverables Functional web application Source code repository Database schema API documentation Deployment documentation Administrator guide User guide Ownership and Intellectual Property All work product, source code, documentation, specifications, workflows, business logic, prompts, training materials, and derivative works developed under this project shall be deemed works made for hire and shall be the sole and exclusive property of the Client. Contractor shall assign all intellectual property rights to the Client upon creation. Contractor shall not reuse, disclose, distribute, or commercialize any portion of the work product without the Client’s prior written consent.

We are looking for an experienced full-stack software engineering team to help architect and build the MVP for a workflow-driven SaaS platform. This is an early-stage startup project with long-term growth potential. We are intentionally keeping the business concept high-level during the initial screening phase and will provide additional details after NDA and qualification discussions. The platform will involve: * Multi-step workflows * User accounts and permissions * Dynamic forms and guided processes * Document management and storage * Dashboard interfaces * Mobile and web support * Notification systems * Payment integration * Audit/history tracking * API integrations * Scalable backend architecture * Future AI/data integration capabilities We are looking for a team that can help: 1. Build the MVP foundation correctly 2. Establish scalable engineering standards 3. Recommend best practices for long-term growth 4. Create a maintainable and scalable architecture from day one? Preferred Stack: * Frontend Web: Next.js * Mobile: React Native + Expo * Backend: NestJS * Database: PostgreSQL * Language: TypeScript We are open to recommendations if there is a strong technical reason for an alternative approach. MVP Goals: * Secure user authentication * Role-based access control * Guided workflow engine * Dashboard UI * File/document upload system * Backend API architecture * Database schema design * Mobile ready architecture * Admin portal * Activity logging/history * Notification system * Payment processing integration * Scalable folder/repository structure * Shared codebase strategy where appropriate * Documentation and handoff standards We’re looking for: * Strong system architecture experience * SaaS platform experience * Experience designing scalable backends * Experience building both web and mobile products * Strong communication * Ability to think through workflows and edge cases * Someone who can challenge assumptions and improve the product technically * Experience working in fast-moving startup environments Nice to Have: * Experience with workflow engines * Experience with compliance-heavy systems * Experience with document automation * Experience with AI integrations * Experience with data aggregation systems * DevOps/cloud deployment experience Please include: * Relevant SaaS projects * Your recommended stack and why * Experience with scalable systems * Whether you recommend monorepo architecture * Experience with React Native + Next.js shared codebases * Estimated MVP timeline * Team structure (if applicable) * Your preferred development workflow/process Bonus if you can explain complex technical decisions in simple business terms.

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.

Conversational AI / LLM Consultant We are looking for a Conversational AI and LLM specialist to support the strategy, design, development, testing, and improvement of AI-powered chatbot and voice automation solutions across multiple business groups. Responsibilities: Help identify, evaluate, and prioritize Conversational AI and LLM use cases across defined business units. Advise on best practices for Conversational AI strategy, LLM architecture, prompt design, orchestration, retrieval, integrations, and development. Recommend improvements across AWS services, Amazon Lex integrations, LLM workflows, and supporting AI infrastructure. Collaborate with the development team on chatbot, voice bot, Lex, and LLM-based implementations and configurations. Conduct QA testing to validate Conversational AI functionality, accuracy, performance, reliability, and user experience. Support the development of solution frameworks, automation workflows, dashboards, application management tools, and fulfillment processes. Assist in designing and extending multilingual Conversational AI solutions in English and Spanish. Support multiple lines of business, call flows, customer journeys, and AI-assisted workflows. Ideal Candidate: Experience with Conversational AI, LLMs, and chatbot or voice automation systems. Familiarity with Amazon Lex and AWS AI services is helpful, but broader LLM architecture experience is equally important. Strong understanding of prompt engineering, AI orchestration, integrations, QA testing, and production AI workflows. Ability to translate business requirements into practical AI-driven solutions. Experience with multilingual conversational design, especially English and Spanish, is a plus.

# Full-Stack AI Engineer — Semantic Search + Next.js + Supabase (Long-Term, Contract-to-Hire) ## About We're building an AI-native platform that makes a large archive of recorded talks genuinely discoverable and useful: need-based semantic search over transcribed media, with a subscription product built around it. We have a clear product vision and architecture and are looking for a lead engineer to build the first version and grow with us long-term. Full product details are shared with shortlisted candidates under NDA — this post focuses on the engineering and the skills we need. ## The engineering challenge You'll build a two-part system that shares one database: 1. **A content pipeline (Python):** ingest recorded talks, transcribe them, chunk and enrich the transcripts with metadata using an LLM API, generate embeddings, and store everything in Postgres. 2. **A web app (Next.js):** fast, crawler-friendly, SEO-strong content pages with structured data; retrieval-based search that returns relevant source material with links/citations; user accounts; and Stripe-gated paid content. We care a lot about retrieval *quality* and clean, maintainable architecture — this is a real product, not a prototype. ## Required tech stack - **App:** Next.js (App Router), TypeScript, Vercel. Strong SSR/SSG, SEO, and JSON-LD structured-data experience. - **AI/backend:** Python; production RAG (embeddings, chunking, retrieval quality); LLM API integration. - **Data:** Postgres + **pgvector** (via Supabase); embeddings via a hosted model (Voyage/OpenAI). - **Auth & gating:** Supabase Auth with row-level security. - **Payments:** Stripe (subscriptions + one-time). ## Required skills - Shipped production Next.js (App Router) + TypeScript apps with strong SSR/SEO. - Built a real RAG / vector-search system in production — not a tutorial clone. - Comfortable in Python for data pipelines. - Postgres + pgvector and Supabase in production. - Stripe integration. - Plans before building; communicates clearly in writing. ## Nice to have - Audio/video transcription experience (Whisper / faster-whisper / Deepgram / AssemblyAI). - Agentic coding workflows (e.g., Claude Code). - Content-heavy SEO products or media libraries. ## Engagement - Hourly, contract-to-hire. ~20–40 hrs/week to start; long-term for the right person. - We start finalists on a **small paid test project** (a single self-contained slice of the pipeline) before the full engagement — that's how we evaluate fit. ## Confidentiality This is a proprietary product. Shortlisted candidates sign a mutual NDA before we share full scope and context. Please don't expect complete product details in the first exchange — strong technical applicants will have everything they need to be evaluated, and the rest follows the NDA. ## How to apply Applications that skip these are ignored: 1. **Start your proposal with the word `pgvector`** so we know you read this. 2. Link **two** projects: one live Next.js/SSR app, and one RAG/embeddings or LLM-integration project. Tell us what *you* personally built. 3. Answer briefly: *An offline embedding pipeline and a live search query must use the same embedding model — why does that matter, and how would you guarantee it?* 4. One line on your approach to chunking long-form audio/video transcripts for good retrieval.

Senior Software Engineer (AI-Focused, Contract – US) Position Summary W Energy is seeking a Senior Software Engineer (Contract) to help drive the integration of AI capabilities into our core platform. This role is focused on building AI-powered product features, not just experimenting with models—embedding intelligence directly into workflows across our upstream and midstream solutions. You’ll design and implement AI-driven functionality that improves automation and user experience. This includes leveraging LLMs, machine learning models, and modern AI tooling within a production SaaS environment. This is a hands-on role for someone who can move quickly, make pragmatic decisions, and bring AI concepts into real, scalable product features. Responsibilities • Design and implement AI-powered features within the platform (e.g., automation, recommendations, copilots) • Integrate LLMs and/or ML models into existing services and workflows • Evaluate, select, and optimize AI tools, APIs, and frameworks for production use • Collaborate with Product to translate business problems into AI-driven solutions • Build and maintain scalable backend services to support AI functionality • Profile, test, and optimize performance of AI-integrated systems • Ensure reliability, security, and cost-efficiency of AI components in production • Contribute to architecture decisions around AI integration and system design • Partner with engineering teams to embed AI into existing applications without degrading stability Requirements • 5+ years of experience as a software engineer in a SaaS or cloud-based environment • Strong backend engineering experience (RoR and/or Golang preferred) • Experience integrating APIs and working within distributed systems • Hands-on experience with AI/ML tools (e.g., OpenAI, Anthropic, Hugging Face, or similar) • Experience building or integrating AI-powered features into applications (not just experimentation) • Strong understanding of data flow, system design, and performance optimization • Experience with relational databases (SQL Server or similar) • Familiarity with microservices architecture, Kubernetes, and CI/CD pipelines • Experience deploying applications in Azure or similar cloud environments • Strong problem-solving skills with ability to work in ambiguous, fast-moving environments • Builder mindset—someone who can take an idea and turn it into a working feature quickly • Pragmatic approach to AI (focus on value, not hype) • Ability to work independently in a contract environment while collaborating closely with internal teams • Strong communication skills and ability to explain AI concepts to non-technical stakeholders Preferred • Experience with prompt engineering, embeddings, or retrieval-augmented generation (RAG) • Exposure to model evaluation, fine-tuning, or AI performance monitoring • Experience with event-driven architectures or real-time data processing • Background in energy, fintech, or other complex data-driven industries

We are seeking an experienced mobile app developer to create a broker-connected mobile application. This app will be designed to read positions, monitor trades, and send alerts, incorporating an AI chat feature. Familiarity with SaaS products is essential. If you have a proven track record of building similar applications and are adept at integrating APIs for real-time data, we want to hear from you. Your expertise will help us deliver a robust and user-friendly solution for our clients.

We are seeking an expert in GoHighLevel to assist with setting up and optimizing our website chat bot AI agent. It is already connected to the website, we just need someone that can help us configure it properly so that potential clients can interact with it

About the Business I own Meet U @ The Net, an established beach volleyball league in Southern California. Website: https://meetuatthe.net The league currently runs multiple seasons per year, has strong player retention, and regularly reaches registration capacity. I am looking for a developer or small team to help modernize the business systems while providing documentation and knowledge transfer so I can eventually manage and improve the platform myself. This is not a one-time project. I intend to build the platform in phases over multiple seasons. Phase 1 Goals CRM Foundation Current data exists across: Excel Airtable Google Sheets The goal is to consolidate historical league data into a single CRM/database. Examples: Players Teams Seasons Registrations Waitlists Payments Participation history Website Rebuild Build a modern website focused on: Registrations League information Schedules Standings FAQ Mobile responsiveness SEO foundation AEO foundation Registration System Support: Individual registrations Team registrations Waitlists Coupon codes Discount codes Payment tracking Waiver System Requirements: Team captains can register teams Individual players must create their own profile Individual players must sign their own waiver Waiver tracking and status management Knowledge Transfer (Required) I do not want a black-box system. I want: Written documentation Loom walkthrough videos Live walkthrough sessions Ability to ask questions after launch The goal is to learn how the system works while it is being built. Future Phases (Not Part of Phase 1) Future projects may include: Scheduling tools Referee score entry portal Automatic standings Sponsorship CRM AI features Mobile applications The initial focus is building a strong foundation. Preferred Technologies Open to recommendations. Currently interested in: Next.js Supabase OpenAI GitHub Budget Approximately: $5,000 – $7,000 for Phase 1 Future phases expected if Phase 1 is successful. Looking For Full-stack developer or small team CRM/database experience SaaS experience Strong communication Documentation-focused Comfortable working with non-technical founders Please send: Relevant projects Technologies used Availability Pricing model Examples of documentation or client training