We are looking for an experienced AI trainer / speaker to deliver a 2–3 hour live, remote Introduction to AI training session for a B2B field sales team The audience will be group of sales professionals. The client is in the protective packaging and packaging automation industry. Their sales team works with customers on packaging materials, packaging processes, damage reduction, labor efficiency, sustainability, throughput, and automation-related opportunities. The goal of the session is to provide a practical and engaging introduction to AI usage in sales workflows. This should not be a highly technical AI course. The focus should be on helping sales professionals understand how AI can support their daily work and improve sales productivity. Desired session focus: Practical introduction to AI and generative AI for non-technical sales users How field sales teams can use AI safely and effectively AI for account research and customer meeting preparation AI for improving discovery questions and understanding customer pain points AI for writing better follow-up emails, summaries, and sales messaging AI for preparing customer-specific value propositions AI use cases relevant to B2B consultative sales Responsible AI use, including confidentiality, accuracy, and human review Live examples and practical demonstrations The ideal trainer should be able to make the session engaging, practical, and relevant to a sales audience. Experience training sales teams, B2B commercial teams, or business users on AI adoption is strongly preferred. Experience in manufacturing, packaging, industrial sales, logistics, automation, supply chain, or similar B2B industries would be a strong plus, but is not mandatory if the trainer can tailor examples appropriately. Trainer responsibilities: Prepare and deliver a 2 hour session Tailor examples to a B2B field sales audience Include practical AI demonstrations that sales professionals can relate to Explain AI concepts in simple business language Provide guidance on safe and responsible use of AI tools Keep the session interactive and engaging for the group Coordinate with us in advance to align the session with client goals Ideal candidate qualifications: Strong experience delivering AI, generative AI, or digital productivity training Comfortable presenting to business and sales audiences Ability to explain AI concepts without unnecessary technical complexity Strong communication and facilitation skills Experience with tools such as ChatGPT, Microsoft Copilot, Claude, Gemini, or similar AI platforms Ability to tailor training examples to client-specific business scenarios Prior experience with sales enablement, B2B sales workflows, or customer-facing teams is preferred Please include the following in your response: Brief summary of your AI training experience Examples of similar business or sales-focused AI sessions you have delivered Your approach for making a 2–3 hour AI session practical and engaging Any relevant industry experience with B2B sales, manufacturing, packaging, logistics, supply chain, or automation Your availability in August for this training session

We're a 30-year, family-owned home improvement company in Michigan. We run a modern but disconnected software stack and we're looking for a developer to connect the pieces, automate manual work, and build reporting that actually gets used. This is project-based contract work to start, with steady ongoing work for the right person. Not a full-time role. What you'd be working on: Our tools don't talk to each other and too much still runs on manual data entry and spreadsheets. We want someone who can look at a workflow, find the bottleneck, and build the fix. Examples of projects on our list: Replace an antiquated Google Sheets scheduling system with something modern and connected Build and maintain integrations between our core tools (CRM, call tracking, phone, accounting) Build BI and reporting dashboards that pull from multiple sources into one clear view Automate manual data entry, lead routing, and reporting tasks Set up AI-assisted tooling where it makes sense (call summaries, automated reporting, data cleanup) Our stack: JobNimbus (CRM, system of record) CallRail (call tracking, ~50 numbers) RingCentral (phone) Rilla (sales conversation analysis) QuickBooks (accounting) Google Ads and Facebook Ads Google Sheets / Google Workspace You should have: Strong experience with API integrations and connecting SaaS tools (Zapier/Make is fine for some of it, but we want someone who can write custom code when the no-code tools fall short) Experience building reporting dashboards or BI tools Comfort with one or more CRM platforms (JobNimbus experience is a big plus) Ability to scope a problem, propose a solution, and ship it without heavy hand-holding Clear written communication and the ability to explain technical work to non-technical people Nice to have: Experience with JobNimbus, CallRail, RingCentral, or QuickBooks specifically Experience building AI-assisted workflows (LLM-based summaries, data extraction, etc.) Experience in home services, construction, or contracting businesses

Engagement Overview I am the CEO and principal attorney of a small law practice specializing in campaign finance, lobbying regulation, FARA, nonprofit law, and government ethics. My five-person team — a junior partner, two associates, and an executive assistant — recently integrated into a larger firm. I am looking for an experienced Claude/AI automation builder for a phased engagement to design, build, and deploy a suite of interconnected agents and automations. This brief covers three phases. Phase I (Inbox Triage) is the highest immediate priority and the natural starting point. Phases II and III follow sequentially. Strong candidates will be evaluated on Phase I but should demonstrate familiarity with the full roadmap. This is a paid engagement. Scope, timeline, and rate are open to discussion. Technology Stack Email: Gmail (personal Pro account — not firm infrastructure) AI: Claude (Anthropic) via MCP or API Task and project management: Notion (existing workspace; routing tables, matter tracking, and timesheet structure already in place) Calendar: Google Calendar Internal chat: Google Chat Document storage: Google Drive (primary); local hard drives on iMac and MacBook Pro (secondary) Matter management / DMS: iManage (larger firm system — integration via dedicated ingestion email address) Voice notes: Plaud (AI note-taker) Signing platform: TBD — candidates should ask during scoping Out of scope: Signal and iMessage — encrypted platforms with no API access; manual forwarding convention only Confidentiality Requirements This is a law practice. Attorney-client privilege and work product protection apply to all client communications and matter-related documents. These are not compliance checkboxes — they are professional obligations with real consequences. The successful candidate must: • Execute a non-disclosure agreement prior to engagement • Demonstrate genuine understanding of why data handling matters in a legal context — not just technically, but professionally • Never use client names, email content, routing data, or document content for training, testing, or demonstration purposes • Work exclusively within the client's authenticated accounts — no third-party data stores outside the approved stack • Design systems that minimize data exposure — process and route, do not store unnecessarily Generic proposals that do not address confidentiality specifically will not be considered.   Phase I — Inbox Triage Agent Real-time classification and routing of inbound Gmail, with a daily digest to the executive assistant. Objective The principal attorney's Gmail inbox receives high volumes of email across clients, matters, and categories of widely varying priority. The goal is an agent that processes every inbound message, classifies it, routes it to the correct person automatically, and ensures nothing drops — without overloading the executive assistant with triage work she should not be doing. Two-Stage Routing Logic Stage 1 — Sender Classification Every inbound email is classified against a tiered contact list maintained in a Notion database: MVC: Most Valuable Clients — 5 to 10 contacts. Highest priority. HVP: High Value People — 10 to 20 contacts. Some overlap with MVCs. Principal attorney, unless task-type rule applies All other clients: Roster managed in Notion with assigned attorney(s). Assigned attorney(s) per Notion client record Catch-All: Anyone not in the contact table — prospects, opposing counsel, vendors, bar association, etc. Generate executive assistant daily digest Stage 2 — Task-Type Classification (MVCs only) For MVC contacts, a second classification layer routes based on the nature of the request. Rules are client-specific. Examples: • Scheduling requests → Executive assistant • Contracts and approvals → Designated associate(s) per client record • Strategic and substantive legal matters → Principal attorney Task-type rules are defined per MVC client and must be configurable without developer involvement. Routing Table — Notion All contact and routing data lives in an existing Notion database. The agent reads from it at runtime. Required fields: • Contact name and/or email domain • Tier (MVC / HVP / Standard / Catch-All) • Assigned attorney(s) for Standard clients • Task-type override rules for MVCs The executive assistant must be able to add, edit, and re-tier contacts without touching code. This is a hard requirement. Routing Output Candidates should propose their recommended approach from among the following, based on current Gmail MCP capabilities: • Apply Gmail label and/or forward to assigned attorney's address • Create a pre-addressed draft for principal attorney review before sending • Log routing decision to Notion with email link and recommended assignee Please address this question directly in your proposal — it is a key evaluation criterion. Daily Executive Assistant Digest Once per day at a configurable time, the agent generates a digest delivered to a designated Notion page covering all catch-all emails from the prior 24 hours. Each entry includes: sender, subject, timestamp, and a one-line AI summary of the email's apparent purpose.   Phase II — 5 AM Daily Brief A structured morning brief delivered to Notion each day before 5 AM, aggregating schedule, tasks, workflow status, news, and forward-looking context. Objective The principal attorney starts each day across multiple locations and needs a single, consolidated view of what matters — professional and personal — without opening email. The brief is delivered to a dedicated Notion page and covers the sections below in the following order. Section 1 — Daily Schedule Full calendar for the day pulled from Google Calendar. All events, calls, and commitments in chronological order. Section 2 — Open Projects and Undone Tasks Two sub-sections: (a) MVC high-value work — open projects and incomplete tasks for Most Valuable Clients, filtered to substantive legal work only; and (b) Personal — all open personal projects and tasks without exception. Personal items are comprehensive by design: if it is not surfaced here, it will be forgotten. Source: Notion task and project database. Section 3 — Blocking What is the principal attorney specifically holding up? Items where others in the firm are waiting for a review, decision, approval, or action. Source: Notion matter and task records where assignee or status indicates the ball is in the principal attorney's court. Note to builder: this section requires careful logic design. The agent must infer from status fields and assignee data what is genuinely waiting on the principal attorney versus what is simply unresolved. Work with client during onboarding to define the exact field logic. Section 4 — News Digest Industry News Curated digest of overnight developments in: campaign finance law and FEC activity, election administration, lobbying regulation (federal and state), nonprofit political activity, and government ethics. Format: short summary of each item with a link to the full article. Aim for signal, not volume — 5 to 10 items maximum. US Political News 5 to 10 headlines with links covering: presidential politics, US Senate and House elections, and major gubernatorial races. Stories people are actually talking about, not wire service filler. Section 5 — Firm Workflow Matter-level status summary pulled from Notion, organized by client tier and activity: Status Definition Closed Completed yesterday Moving Action taken yesterday Paused No action yesterday Stuck No action in five or more days Client groupings: MVCs (non-high-value work), Standard clients (all work), and any other open matters. Section 6 — One Month Look Ahead Rolling 30-day forward view pulled from Google Calendar covering: regulatory filing dates and compliance deadlines, matter-level deadlines, client birthdays, holidays, and planned vacations or travel. Anything that requires preparation or awareness in the next 30 days. Section 7 — Personal Financial Summary (If Feasible) Summary of personal financial position pulled from Monarch Money, if an API or MCP connector is available. Candidates should investigate Monarch's API access and address feasibility in their proposal. If not currently feasible, this section is omitted without affecting the rest of the brief. Delivery Notion only — not email. A dedicated page refreshed each morning before 5 AM. Previous day's brief should be archived, not overwritten.   Phase III — Night Maintenance Three nightly agents that run after close of business: timesheet creation, document filing preparation, and Plaud note routing. All outputs are delivered to Notion for principal attorney review. Part 1 — Timesheet Creation Objective Each evening, the agent reviews the day's activity across three sources and populates a timesheet in an existing Notion template for the principal attorney's review and finalization. Sources • Google Calendar — all events and calls attended • Gmail sent items — emails sent that day, grouped by client/matter where inferable • Google Chat — internal messages sent, grouped by thread/matter where inferable Note to builder: Google Chat API access will need to be confirmed alongside Gmail and Calendar MCPs. Confirm availability and any OAuth scope requirements in your proposal. Output: Populated Notion timesheet using existing template structure. Principal attorney reviews each morning, adjusts entries as needed, and finalizes. The agent does not finalize — it drafts. Part 2 — Document Filing Objective Each evening, the agent surfaces documents created or edited that day for the principal attorney's review. The attorney flags finals, and the agent forwards them to the firm's iManage ingestion email address for filing. Sources • Google Drive — documents created or modified that day • Local hard drives — iMac and MacBook Pro Note to builder: local hard drive access requires a locally-running component (daemon, Claude Code instance, or folder-watching script) on each machine. Please address your proposed approach to this in your proposal. Alternative approach for consideration: a designated 'Ready to File' folder on each machine that syncs to Google Drive. The attorney drags filing-ready documents into this folder throughout the day; the agent watches the folder and processes from there. Simpler architecture, device-agnostic, and builds a consistent filing habit. Candidates should evaluate and recommend. Output: A Notion page listing all documents surfaced for that day, with document name, location, and last-modified time. Principal attorney marks finals. Agent forwards marked documents to the iManage ingestion email address. iManage filing is handled by firm IT from that point — no direct iManage API integration required. Part 3 — Plaud Note Routing and Archiving Objective: The principal attorney uses a Plaud AI note-taker on calls and meetings. Each evening, the agent pulls new Plaud summaries, routes them to the appropriate team members, archives a copy to Notion tagged to the relevant client matter, and deletes the underlying audio and transcript from Plaud's platform and the local device. Prerequisite — Plaud API Plaud API or webhook access is a prerequisite for this part. Candidates must investigate and confirm availability before scoping. If Plaud does not currently support programmatic access, this part will require a manual export step as a workaround — please address both scenarios in your proposal. Routing Logic: Similar in structure to Phase I inbox triage routing (MVC/HVP/Standard tiers with task-type overrides) but with distinct rules to be defined with the client during onboarding. Do not assume inbox triage rules apply directly. Archiving: One copy of each Plaud summary is saved to Notion as a note, tagged to the relevant client matter. Tagging logic to be defined during onboarding. Deletion: After successful routing and archiving, the agent deletes: (a) the audio and transcript from Plaud's platform via API, and (b) any local copies on the principal attorney's devices. Local deletion requires the same locally-running component described in Part 2. Candidates may propose a unified local agent that handles both Part 2 and Part 3 local operations.   What I'm Looking For Strong candidates will have: • Demonstrated experience building Claude-based automations or agents — not general AI experience • Hands-on experience with Gmail MCP, Google Calendar MCP, and Notion MCP (or equivalent API integrations) • Ability to build systems that non-technical users can maintain — editability and simplicity are as important as technical sophistication • Comfort with phased delivery — Phase I first, Phases II and III following sequentially based on performance • Experience with professional services clients (legal, financial, consulting) is a meaningful plus • Willingness to execute an NDA and work within a legally sensitive environment What to Include in Your Proposal Please address the following specifically. Proposals that do not engage with these questions will not be considered. • Your proposed technical architecture for Phase I — how you would connect Gmail, Claude, and Notion • Your answer to the Gmail MCP routing output question in Phase I (labeling vs. drafts vs. Notion logging) — what is actually supported and what do you recommend • Your assessment of Plaud API availability and your proposed approach for Phase III Part 3 • Your assessment of Monarch Money API feasibility for the Phase II financial summary section • Your proposed approach to local hard drive access for Phase III Parts 2 and 3 — daemon, sync folder, or other • A comparable project you have delivered — describe the client type, the stack, and what made it work • Your estimated timeline and rate for Phase I, and a rough order-of-magnitude estimate for Phases II and III • Confirmation that you are willing to execute an NDA prior to engagement I am looking for someone who has read this brief carefully and has a specific, informed point of view on how to build it. This is phase one of a longer automation roadmap and the right candidate will be a long-term partner, not a one-time contractor.

Deliverable Requested from Developer Build a Google Workspace solution that: 1. Monitors incoming emails in slab-sewer@, rough@, and trim@ 2. Uses AI (Gemini, OpenAI, or similar) to classify severity and category 3. Automatically applies Gmail labels 4. Marks RED items as important 5. Runs automatically every few minutes 6. Requires no action from Project Coordinators Success Metric: A Project Coordinator can open their inbox and instantly identify which emails require immediate action versus which can wait until later in the day, without manually reading and sorting every message.

**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

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.

Guardian Senior Solutions GoHighLevel + Retell AI Build — Job Posting & Scope of Work Posted by: Paul · Guardian Senior Solutions (GSS) Orange County, California — remote contractor accepted Project overview Guardian Senior Solutions (GSS) is a direct-to-consumer senior care navigation platform in Orange County, California. We are a conflict-free alternative to referral platforms like A Place for Mom — we coordinate care, legal, financial, and home equity needs for senior families rather than operating as a care provider ourselves. We need a GoHighLevel (GHL) build that automates our lead-to-appointment pipeline end to end: from the moment a lead comes in (web form, paid ad, social DM, referral) through AI-driven outreach (voice via Retell AI, SMS, email) to a booked assessment appointment with one of our case managers, by phone or in person. This is a real-time-sensitive use case — families reaching out are often in or near a care crisis, so speed and reliability of follow-up directly affects whether we can help them. What success looks like • A lead that fills out a form, comments on a social post, or calls in gets a response within 5 minutes, every time, with no silent failures. • Qualified leads are automatically routed into a clear pipeline and booked onto a case manager's calendar without manual intervention. • We can see, in one dashboard, exactly where every lead is and whether any have gone stale. • The system is documented well enough that we are not permanently dependent on the person who built it. Scope of work 1. Core GHL architecture • Build a 6-stage lead pipeline: New Lead → Contacted → Nurturing → Appointment Booked → Consultation Complete → Not Ready / Lost. • Configure custom fields: care urgency (1–5), who care is for (self / parent / spouse), homeowner Y/N, estimated home value, legal documents in place Y/N, lead source. • Set up lead source tagging across all channels: Google Ads, Meta Ads, organic/social, referral partner (by name), direct, and any purchased lead lists. • Build a reporting dashboard tracking: leads by source, speed-to-contact, appointment conversion rate, show rate, and pipeline value by stage. 2. Retell AI voice integration • Integrate Retell AI with GHL so that a new lead triggers an outbound AI voice call within 5 minutes of form submission. • Build fallback logic: if the call is not answered, automatically fall back to SMS rather than silently dropping the lead. • Configure the call outcome (answered / voicemail / booked / declined) to write back into the GHL contact record and move the pipeline stage accordingly. • Work with us to finalize the AI voice script and qualifying questions (we have a draft framework already). 3. Lead nurture automation • Build the speed-to-lead workflow: AI call + SMS on form submit, second call attempt at 1 hour, email at 2 hours, manual task created for a human follow-up at 24 hours if still unresponsive. • Build a 21-day nurture drip for leads not yet ready to book, mixing educational email content with SMS check-ins (content outline will be provided). • Build appointment confirmation and reminder sequences (instant confirmation, 24-hour reminder, 1-hour reminder) via email and SMS. • Build a post-consultation follow-up sequence including a same-day summary, a 3-day check-in, and a 7-day review request (conditional on a positive-outcome tag). 4. Social + email content engine • Set up GHL's Social Planner across Facebook, Instagram, LinkedIn, and TikTok with an approval workflow so content is AI-drafted but human-approved before publishing. • Set up a weekly email campaign workflow: AI-assisted draft, human approval step, then send. • Connect inbound engagement (Facebook/Instagram DMs and comments, web chat, SMS, email replies) to GHL Conversations and route qualified leads into the Conversation AI for qualification. • Flag clearly in writing if TikTok DM-to-CRM integration is not currently supported natively by GHL, and propose a workaround if one exists. 5. Appointment booking & case manager routing • Integrate calendar booking (Calendly or GHL's native calendar) so qualified leads can be booked directly onto the correct case manager's calendar, distinguishing between phone and in-person assessment appointment types. • Build routing logic if we have more than one case manager (e.g., by territory, availability, or caseload). 6. Reliability, testing, and handoff • Idempotency checks so a lead submitting twice, or a webhook firing twice, does not trigger duplicate calls or duplicate pipeline entries. • A staging/test mode so new or modified workflows are tested with dummy leads before going live. • Monitoring or alerting so we are notified if a workflow breaks or a lead has gone untouched for more than 2 hours. • Full written documentation of every workflow, automation, and integration built, in plain language we can hand to a future hire if needed. • A 30-minute live walkthrough/training call upon completion. Requirements • Demonstrated prior experience integrating Retell AI (or a comparable AI voice platform) with GoHighLevel. Please describe your specific integration approach in your application — this is the single most important qualifier for this role. • Strong working knowledge of GHL workflows, pipelines, Conversations, Social Planner, and custom fields. • Experience with webhook-based integrations and basic error handling / fallback logic. • Prior experience in healthcare, home services, senior care, or another high-urgency, high-trust service business is a strong plus. • Clear, responsive communication — we will be working closely together through build and testing. How to apply 1. Confirm you have integrated Retell AI (or similar) with GoHighLevel before, and briefly describe how you approached it. 2. Share 1–2 examples of GHL builds you've done for service businesses, ideally with multi-channel lead nurture. 3. Provide your estimated timeline and a flat-fee quote for the full scope above (we prefer fixed pricing over hourly for this project). 4. Let us know your availability to start. We have a detailed internal spec (pipeline stages, message templates, and workflow logic) ready to share with serious candidates upon request.

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

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.

We are seeking a hands-on AI systems expert to help us establish, secure, and scale our internal AI capability. The role involves both technical implementation and advisory responsibilities, with the expectation of staying on as a trusted advisor. The ideal candidate will have a strong background in AI systems and be able to provide strategic guidance.