Project Overview We are building an AI-powered voice receptionist agent for a dental practice client. The agent will handle inbound calls 24/7 — booking, rescheduling, and canceling appointments, answering FAQs, and escalating complex situations to a human. The voice layer is built in Retell.ai and the orchestration/automation flows run in n8n, with integration into a dental practice management systems. This is a hands-on build role, not consulting. You will design, configure, and iterate the agent working directly with our founding team. What You'll Build: Conversational voice flows for new and returning patients (booking, rescheduling, cancellations, FAQs, insurance questions, urgent/emergency triage) Clean escalation paths to human staff when the agent can't handle the call n8n workflows connecting the voice agent to the practice management API for real-time schedule reads/writes HIPAA-conscious configurations and tool choices throughout the stack Performance tracking and iterative prompt/flow improvements based on real call feedback Seeking an Expert Who: You've built multiple production voice agents, ideally in healthcare or dental, and can own the full stack from architecture to delivery. You think critically about latency, barge-in behavior, edge cases, and HIPAA compliance — not just happy-path flows. Requirements: Deep expertise in Retell.ai — prompt tuning, latency optimization, interruption/barge-in handling, LLM selection, and cost modeling Advanced n8n automation — complex branching logic, dynamic data handling, external API integrations, and error recovery Experience with dental or healthcare organizations — you understand how practices operate, what front desks actually deal with, and how to translate that into agent logic HIPAA awareness — you know which tools and configurations are appropriate for PHI workflows Track record of full-cycle delivery: scoping → build → pilot → iteration Nice to have: Dentrix Ascend integration, NexHealth, prior AI receptionist or appointment-booking agent for a clinic/practice. 📋 To Apply, Please Answer Have you built a production voice agent with Retell.ai? If yes, briefly describe it. What's your approach to managing Retell.ai per-minute costs on an inbound call agent? Have you worked with dental or healthcare clients before? What was the workflow? Paste a relevant n8n workflow screenshot or describe your most complex flow.

I need a advanced agentic system built with persistent memory and up to 6 agents that work together. I am building a franchised coffee shop business. there is so much data that can be pulled together and harvested from customer spending habits and also what is the highest grossing items that sell , vs the most profitable hours of the day. All that data needs to be meshed with the actual Quickbooks data and financials. All that then needs to be balanced with real world site selection for new coffee shop locations. Here is what I need: Agent 1. Pulls information Directly from clover POS automatically. Agent 2. takes Agent's 1 information and cross references with Margin Data from Quickbooks. Recommends New drinks that are both on trend AND High Margin. Agent 3 is the financial Agent. It works directly with Quickbooks. It monitors cash flow and alerts when labor percentage exceeds parameters. It also stress tests expansion and " what if" scenarios. Agent 4. the site selection agent. agent 4 monitors LoopNet, Costar, and parcel data for commercial land available. It cross references traffic count and demographics, it checks competitor coffee presence etc. Agent 5 is the capital strategist. when agent 4 finds a location, it consults with agent 3 which is connected to Quickbooks , it models out loan scenarios, cash flow impact. and helps run " what if " scenarios that it gets asked. Agent 6 is the main Orchestrator that runs everything that I would communicate soley with through Whatsapp. It connects all the agents and pulls data collectively and makes them all work together and stress tests ideas that one agent might find.

I am looking to partner with a competent dev team (individual or team) to launch AI implementation solutions for small and medium-sized businesses. As a sales professional, I aim to provide innovative solutions that enhance business operations. The ideal candidate will have experience in AI technologies and a strong understanding of business needs.

Overview We run an AI voice assistant for self-storage operators. We have an internal, AI-assisted workflow for triaging call feedback — investigating what happened on a call, diagnosing the root cause in our codebase, and drafting fixes. We’re looking for someone technical to run that AI-assisted workflow day to day and help us make it better. You’ll be driving AI coding agents, reading real code to understand behavior, and improving the process and tooling itself. What you’ll do Use our AI agent tooling to work through a queue of customer feedback on AI voice calls. Read our TypeScript/Node codebase (voice-agent prompt assembly, workflow/“SOP” engine, tool implementations) to diagnose why the agent behaved a certain way — not just guess. Draft fixes: workflow-instruction edits, knowledge-base entries, or code changes via pull request with a clear verification plan. Improve the triage process itself — refine the AI agent prompts/skills, conventions, and the internal MCP tooling that powers it. Write clear, customer-facing summaries of what changed for our team to review and approve. You’re a great fit if you Read and reason about code confidently — ideally TypeScript/Node; React a plus. Have hands-on experience driving AI coding agents (Claude Code, Cursor, or similar) and understand how LLM prompts/tools/agents fit together. Think in cause-and-effect: “the agent did X because line Y / instruction Z.” Write precisely and concisely for both technical and non-technical audiences. Are process-minded — you spot the repetitive thing and turn it into a better workflow. Bonus: prompt engineering, LLM tool/agent development, or voice/conversational AI experience. How we work We’ll start with a paid trial on a small batch, then scale steady ongoing volume. To apply: Tell us about a time you used an AI coding agent to diagnose or fix something non-trivial in a codebase you didn’t write — what you did, and how you verified it worked. A link to relevant work is a plus.

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.

Project Overview We are looking for an experienced AI workflow, process design, and prompt engineering expert to help us automate part of our sales and proposal development process. Currently, our project management team spends 4–12 hours developing a custom research plan and proposal for each active FSI lead. In busy weeks, we may work on 5–6 leads, which creates a significant time burden and slows down response time. We want to build a custom ChatGPT skill or AI workflow that can take sales notes, email context, and call notes, then help generate a research plan and proposal in our existing format. What We Need We need someone who can: Learn and map our current sales/proposal process Translate that process into a structured AI workflow Write effective prompts and decision trees Train or configure a custom ChatGPT skill/workflow Help the AI ask the right follow-up questions Generate proposal sections based on uploaded notes Recommend research scope, segmentation, targets, and options Output the final proposal in our existing template Desired Workflow The ideal AI workflow would allow us to upload notes from emails and sales calls. The AI would then ask a series of structured questions to determine how to write each section of the proposal. The AI should be able to: Recommend the appropriate research process Suggest project scope Identify demand segmentation opportunities Create tables for the proposal Recommend constituencies and companies to target Suggest research options Draft the proposal using our template Provide a strong first draft that our team can review and adjust Business Goal The goal is to significantly reduce the time spent developing research plans and proposals, especially for early-stage leads and marketing-generated opportunities. This is particularly important for new leads from companies we have not worked with before, where the probability of closing may be relatively low. We want to respond quickly and professionally without taking excessive time away from active client projects. Ideal Freelancer You should have experience with some or all of the following: AI workflow design Prompt engineering Custom GPTs or ChatGPT skills Sales/proposal automation Business process documentation B2B research or consulting workflows Template-based document generation AI-assisted decision trees Knowledge management or internal AI tools Experience with market research, consulting, or proposal development is a plus. Deliverables We expect the freelancer to deliver: A documented AI workflow/process map A set of structured prompts and instructions A functioning custom GPT, ChatGPT skill, or equivalent AI workflow Question logic for gathering missing proposal inputs Proposal section drafting logic Testing and refinement using sample lead notes Documentation so our team can maintain and improve the workflow Project Type This will likely begin as a one-time project, with potential for ongoing support as we refine the workflow and expand it to other proposal types. To Apply Please include: Examples of AI workflows, custom GPTs, or prompt systems you have built Your experience with proposal automation or business process automation Your recommended approach for this project Any questions you would need answered before starting

We are an investment firm with a portfolio of healthcare companies. We are seeking to begin building our data capture systems across our business and layer AI to surface summarize and store insights. This is a process that is in parallel to our operations team SOP'ing our process in anticipation of expansion. It is our opinion that we have a relatively simple business process from end to end and lots of potential to capture useful data signals across each department/function. We have drafted a rough business process / data ontology diagram showing our preferred approach. We are seeking an expert to: 1 ) Create lightweight data systems to capture data signals from end to end across our business (Recruiting to Onboarding to Scheduling to Payroll to Finance to Legal to). This also includes organizing and categorizing our past / existing data in addition to capturing signals for future data. 2 ) Layer AI / agentic AI automations that can surface insights, categorize and aggregate info, populate knowledge databases, etc. Example Data Signals / Use Cases: Fireflies recorded meetings Tagging emails in inbox as Legal/Finance/Scheduling/Onboarding etc Job Board Postings Airtable (For building a lightweight scheduling/employee management system) (For storing a knowledge database and rolodex) To Apply: Please briefly present an instance of implementing a similar lightweight solution to capture data signals and convert the data into meaningful and actionable insight via AI

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.

We are looking for an experienced full-stack developer with strong AI-assisted development skills to help us transform our existing payment administration web platform into a modern application. We operate a payment management/admin system and want to accelerate development using AI tools such as Cursor, Claude, ChatGPT, GitHub Copilot, or similar technologies. The goal is to rapidly build, improve, and scale our payment administration platform while maintaining high code quality and security standards.

We’re hiring an extraordinary developer to own and grow our Base44 apps and sales products. around the future of AI discovery 1. Future of AI Discovery Core Demo – https://pull-discovery-core.base44.app/ You’ll evolve https://pull-discovery-core.base44.app/ into a beautiful, fluid, high‑performance, full-functional future of AI discovery demo following our advanced and sophisticated technical blueprint Integrate and orchestrate AI models incorporating LLM's, Search and World Models into a seamless experience with no visible seams between UX and intelligence. Own front‑end performance, responsiveness, and micro‑interactions—animations, transitions, and state changes should feel intentional and “alive,” not bolted on. Implement robust logging and analytics to understand how users explore, where they get stuck, and how the discovery engine can adapt dynamically. 2. Book Sales Engine – Six‑Channel Publishing System The second current Base44 project is a system that operationalizes our comprehensive sales plan across six channels. SEE THE COMPREHENSIVE BOOKSALES PLAN ATTACHMENT UNDERNEATH THIS POSTING You will: Translate a detailed multi‑channel publishing strategy (KDP optimization, physical bookstores via IngramSpark, other digital platforms, libraries, bulk institutional sales, and authority‑engine content marketing) into concrete workflows, tools, and dashboards. Build internal interfaces and automations to: Track metadata, pricing, and promotions across Amazon KDP and other platforms. Monitor campaigns across TikTok, Meta, LinkedIn, YouTube, newsletters, and partnerships. Surface KPIs like BSR, review velocity, ad spend, email growth, library adoptions, and bulk orders in a single, coherent view. Design light internal UIs that make it easy for non‑technical team members to update copy, add titles, trigger campaigns, and view performance without breaking anything. Implement robust, testable integrations between Base44, external APIs, and data sources to keep everything in sync as we scale from 8 to 22+ titles and beyond. Who You Are We’re not looking for a generic “full‑stack dev.” We’re looking for an unusual combination of visionary and doer: Creative technologist mindset – You think in systems and interfaces at the same time. You care deeply about how a product feels as well as how it works. Obsessed with execution – You’re disciplined, structured, and relentless about shipping. You break ambiguity into sprints, reduce complexity into tickets, and never let projects stall. Proactive owner – You don’t wait for instructions. You propose better ways to do things, flag risks early, and bring options—not problems—to every conversation. Strong product sense – You can balance ideal UX with realistic constraints and understand when to ship v1 vs. when to invest in polish. Comfortable with complexity – Multi‑channel distribution, layered data flows, and evolving requirements don’t scare you; they energize you. Ideal Skills & Experience You don’t need all of these, but you should recognize yourself in most: 5+ years building production web applications, ideally with a strong front‑end/UI focus. Deep experience with modern web stacks (React/Vue/Svelte or similar) and TypeScript, plus comfort with Node or comparable back‑end runtimes. Strong visual/UI instincts: experience collaborating with designers or owning design yourself for data‑rich interfaces and dashboards. Experience integrating AI/LLM APIs and retrieval systems into real products (RAG flows, multi‑step tool use, chat‑like interfaces, recommendation engines). Experience with analytics and experimentation: event tracking, funnel analysis, A/B testing. Familiarity with publishing, ecommerce, or multi‑channel marketing systems is a plus (KDP, IngramSpark, email platforms, ad platforms, analytics). Prior work in environments like Base44 or other low‑code/agentic platforms is a strong plus, but not required if you learn fast.