Made a small video breaking how to design a converting outbound pipeline that that works for voice AI agency owners. Hope its helpful.

I was in the Voice AI agency space for close to a year. But outbound prospecting was something that always got in my nerves I knew businesses need Voice AI service but never was sure who had it, who didn't and whom to pitch So I built a startup around this problem The automation calls businesses after hours to make sure they are not using AI, then finds the owner's email, finds out what pain point they have and why they need voice AI, Pain point are calculated based on their :- 1. Higher call volumes which likely results in missed calls, 2. If they are investing in paid inbound leads by running ads, they might be paying for something they are missing 3. If their customer complained about their phone not being picked in the review 4. If they are using tools like CallRail, Weave, Dialpad, Tido, they know call matters and might be open in investing in missed calls These are the primary reasons Then pushed into the CRM. Per niche, 50 leads a day, 375 leads a week and 1500 leads a month I just finished development like 10 days ago, I am working as a solo founder in this team, If you guys are voice Ai agency owners yourself, would you use this service? Tell me And do you know anyone who might be interested in this? www.groveagents.com

Seeking a Commission-Based Sales Partner 💼 I develop AI-powered calling receptionists for local businesses — think medspas, dental clinics, barbershops, and beauty clinics. The AI handles inbound calls and books appointments automatically, around the clock. The product sells itself. I just need the right person to get it in front of decision-makers. What's in it for you: → 40% commission on every deal you close → No earnings cap — close as many as you want → Full demo + closing script provided → No technical background needed Interested in a high-ticket commission opportunity in one of the fastest-growing spaces right now? DM me or comment below. 👇

Hey everyone, I'm building an AI automation product for e-commerce store owners and looking for a reliable technical VA to help onboard new clients. What the work involves: - Setting up API keys (Shopify, Google Ads, Meta, GA4, Telegram) - Deploying to Railway (simple deployment, full guide provided) - Configuring environment variables (.env file) - Copying agent files to the right directories - Creating Telegram bots via BotFather - Running a final checklist to confirm everything is working You don't need to build anything. Full step-by-step documentation will be provided. You just follow the guide. Each onboarding takes around 45–60 minutes. Skills needed: - Comfortable with terminal / command line - Basic understanding of APIs and environment variables - Familiar with Railway or similar deployment platforms - Shopify basics - Detail-oriented - following a checklist precisely matters here Pay: $30 per client onboarded initially If this sounds like you, drop a comment or DM me. Happy to hop on a quick call to walk you through the process.

Automation Doesn’t Fail Because of Tools It Fails Because of These Things Most broken automations weren’t built wrong technically. They were built wrong conceptually. Here’s what actually matters. 1. Ownership must be clear Every automation needs an owner. Not “the system”. Not “the tool”. A real person who is responsible when it: misfires sends the wrong message misses a lead If no one owns the automation, no one improves it. 2. Timing is more important than speed Fast automation is useless if it’s badly timed. Following up too early feels pushy. Following up too late feels careless. Good automation respects: business hours response gaps user behavior Timing creates trust. Speed does not. 3. Exceptions are the real workload Automation handles the average case easily. The value is in handling: incomplete data unexpected replies edge cases If your system breaks on exceptions, you haven’t automated — you’ve postponed work. 4. Feedback loops are essential Automation without feedback never improves. Your system should learn from: replies failures manual corrections Even simple feedback (tags, notes, outcomes) can dramatically improve future decisions. :--> Questions:+ 1. More points to add ? 2. More points to improve? 3. Which point is mostly happens?