AI-Enhanced Communication Channels For Support

Is #VoiceAI the #NextBigThing for businesses since the #internet boom of the 90s? 🤖 I genuinely believe so. We're on the cusp of a massive change in how we interact with technology. Remember when every business suddenly needed a website? I see the same thing happening with voice AI by 2026. We're moving beyond simple voice commands. We're building #AIAgents that can truly understand conversational context, speak like a human, and, most importantly, act. Think about an Voice enabled #ConversationalAI that can: 💎 Search the web for you 💎 Update your customer database in real-time 💎 Send follow-up emails 💎 Book appointments and manage calendars This isn't science fiction; it's what's possible right now. I recently built a #demo for a client to showcase exactly this. I created an outbound calling system that contacts their customers and partners, asks relevant business questions, and instantly updates their database with the new information. No more manual data entry, no more outdated records. Check out the video to see it in action! 👇 This is just one example. The potential use cases are huge: 📞 Automated Surveys: Gather customer feedback on products and services effortlessly. 🤝 Sales & Outreach: Pitch new solutions to potential customers. 🛎️ Virtual Office Assistant: Handle incoming calls, answer customer questions, and book appointments 24/7. The goal is to create a better overall #CustomerExperience and free up valuable time for your team, resulting in #OperationalEfficiency and #Productivity jump. 👨💻 Curious about the #tech behind it? 👨💻 In simple terms, the system uses a backend to initiate a call through a #WebRTC platform (I used LiveKit, but others work too). This platform then connects to our backend "worker node" that asks the #Livekit to dial the number via Twilio #SIP to reach the person on the regular #PSTN phone network. Once the call is answered, the system cleverly adds the Voice AI agent into the conversation. From there, the person and the #AI can talk naturally. When the call ends, the system cleans up everything automatically. The best part? It's built to scale. By containerizing the worker nodes (think of them as little self-contained packages of code using #Docker) and managing them with something like #Kubernetes, the system can handle thousands of simultaneous calls without breaking a sweat. If things get busy, it just spins up new workers to handle the load. It's a seamless and powerful #architecture. I'm incredibly passionate about AI in general and its potential to revolutionize how businesses operate. If you found this #demo #insightful, I'd appreciate it if you'd like, comment, or share it with your network! What are your thoughts on this? Do you see Voice AI becoming a standard tool for businesses? Let's discuss in the comments! ⬇️ #VoiceAI #ML #MachineLearning #ArtificialIntelligence #FutureOfBusiness #Innovation #Automation #OutboundCalling #AISDR #LLM #CustomerService #AISales #AgenticAI

Generative AI has been making waves in the industry for over two years, revolutionizing how businesses engage with customers. In this blog, the Engineering team at Noom shares how they developed their AI-powered customer support solution. Noom is a digital health company offering a subscription-based mobile app that helps users achieve their wellness goals, and it relies heavily on its chatbot for customer interactions. While directly leveraging ChatGPT-4 for customer chats was a promising first step, the team identified several challenges: issues with hallucinations, a lack of customization to user needs, and a mismatch with Noom's unique communication style. To address these challenges, the team developed a customized solution. They started by using Prompt Instruction with GPT-4 to form the foundation of their AI assistant. Next, they implemented Prompt Augmentation with Noom's Knowledge Base (RAG), Dynamic Prompts based on user data, and JSON Format Responses. These elements enabled the system to accurately process user messages, understand their needs, and deliver tailored responses. Furthermore, recognizing the importance of human connection, the team integrated classification models with LLMs to identify when a human touch was needed, ensuring users felt understood and valued. This approach is a great example of companies leveraging generative AI to create customized solutions that address their unique challenges. #datascience #machinelearning #generative #LLM #chatGPT #customer #chatbot – – –  Check out the "Snacks Weekly on Data Science" podcast and subscribe, where I explain in more detail the concepts discussed in this and future posts:    -- Spotify: https://lnkd.in/gKgaMvbh   -- Apple Podcast: https://lnkd.in/gj6aPBBY    -- Youtube: https://lnkd.in/gcwPeBmR https://lnkd.in/gvJg5tMK

Came back from vacation Monday. Inbox? On fire.🔥 Buried in the chaos: a customer story that stopped me in my tracks (and made me so happy). A Customer Support leader at a fast-growing financial services company used AI to transform his team - in just a few weeks. This leader works for a financial services company that’s in high-growth mode. Great news, right? Yes! For everyone except his Customer Support team… As the business grew faster, they were bombarded with repetitive questions about simple things like loan statuses and document requirements. Reps were overwhelmed. Customers faced longer response times. The company has been a HubSpot customer for nearly 10 years. They turned to Customer Agent, HubSpot’s AI Agent, and got to work: - Connected it to their knowledge base → accurate, fast answers - Set smart handoff rules → AI handles the simple, reps handle the complex - Customized the tone → sounds like them, not a generic bot (you know the type) In a short space of time, things changed dramatically: - Customer Agent now resolves more tickets than any rep - 94.9% of customers report being happy with the experience - For the first time, the team can prioritize complex issues and provide proactive support to high-value customers It’s exciting to see leaders using Customer Agent to not just respond to more tickets, but to increase CSAT and empower their teams to drive more impact. 2025 is the year of AI transformed Customer Support. I am stunned by how quickly that transformation is playing out!