As mentioned in the title, I just delivered a project which is a 24/7 Voice AI Inbound Receptionist for trade businesses. Took me about two months working closely with my client and I implemented it using Vapi, n8n, as well as Simpro, which is a field service management software specifically for the trades. The entire system does the following: - Answers inbound calls automatically - Handles job bookings, rescheduling, cancellations - Forward calls to person in charge in case of emergencies - Answers general enquiries - Creates or updates records directly inside Simpro The goal was simple: Reduce missed calls and automate admin while technicians are on-site working. In total, my client paid me just over $2,000 for this implementation and service, it's definitely a huge win for me. Happy to connect with anyone exploring Voice AI automation for service businesses. ps. You can check out this website for the demo recordings: https://simpro-voice-agent.com/ pss. I would love to share a screenshot of the n8n workflows but I think my client's VPS server is down as of writing 🫠

Hi guys, I'm new to building Voice AI agents so I would need help. I'm currently building a custom project for my client. I've attached a diagram so that it's easier to visualise. Let's keep it simple for now and just focus on the Voice AI section: He essentially wants a simple high level agent that decides the intent of the inbound call. Customer looking for support --> Customer Support Agent Customer interested in their services/product --> Sales Agent Customer has billing issues --> Financial/Admin Agent ... and maybe more agents (potential for scale) I think my main decider between all the Voice AI platforms available would be the agent transfer/routing feature, ease of use, and maintainability. Here are my thoughts and experience so far: Vapi - Overwhelming. Really developer centric. I think I have to manually integrate RAG on n8n/make.com? Can't seem to make routing and transfering work for some reason. ElevenLabs - So far the new Workflow feature does what I want. Just slightly clunky at the moment. Might be too pricey for my client. Retell AI - Has agent transfer feature. Probably by far the most promising of them all. Synthflow - Not sure how to get multi-agent thing to work just yet, or you probably can't? But you can use one agent for Voice/WhatsApp/Email/Widget. Curious what you guys think. Do let me know if there's anything else I need to clarify :)

Hey everyone 👋 I’m looking to collaborate with businesses, creators, or agencies who want to automate parts of their work. I’m offering my help for free (or at a very low cost if you’d like to support me) in exchange for a testimonial 💬 💡 What I Build: - 📊 Smart finance tracking workflow (check out my Loom demo! It’s an original project I use personally.) - ⚙️ Systems that automate everyday tasks like lead tracking or client onboarding - 🔌 Integrations using tools like Notion, Cal.com, Google Sheets, and OpenAI via Make or n8n I’ll be real. I’m new to real-world AI automation projects. But every mentor and YT creator says the best way to learn is by doing, not endlessly preparing. So here I am, taking that step 😬 If you’ve got a project or idea that could use some automation, I’d love to help out. You’ll get a working system, and I’ll get to learn and grow through the process. And if you don’t like it, it costs you nothing :) So let’s build something together 💪 DM or comment if you’d like to chat or see what I can build! p.s. I’m definitely open to long-term partnerships 👀

Today I worked completely on the RAG Platform and checked on different ways to increase the retrieval speed! I started with using Supabase as my vector DB, Local Embedding Model(nomic-embed-text) and I also added a contextual ingestion method! This method is like you have a chunk and you provide that chunk to the llm with the whole document and the llm provides you a context that you can add with that chunk to increase the accuracy! Then, My Mentor suggested on using Redis Vector Store, and it worked really well! The retrieval was really quick and it worked really well! Now, I'm just waiting for the approval to start working on the V2 of the project and connect the Platform with a Database, and expose API's for the frontend! Thats it for today! let me know what you think! #RAGPlatform #VectorDatabase #Supabase #RedisVectorStore #LocalEmbeddingModel #NomicEmbedText #ContextualIngestion #AIIngestion #RAG #LLMIntegration #LearningInPublic #Day50 #DatabaseIntegration #APIDevelopment #FrontendIntegration #AIWorkflow #TechJourney

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