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Built an AI-powered RAG platform trained on structured datasets to deliver intelligent recommendations, semantic search, eligibility reasoning, and grounded conversational responses through a modern chat-based interface.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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UI and the color scheme look 🔥 Where are you designing it?
Project Name: Tell me a story Dad/Mom
Template Link: https://elevenlabs.io/app/templates/SdRrbRVrYdABebMSyFto
Social Media Post: https://www.linkedin.com/posts/jose-arturo-6b5507332_elevencreative-activity-7461639238644572160-84QG?utm_source=share&utm_medium=member_desktop&rcm=ACoAAFO5jykBCSk0VemkPNBaENwE-LE_0HIHznU
Description: An interactive, age-gated AI storybook template tailored to early childhood psychological milestones, featuring instant parent voice cloning and animated sequential dialogs.
Process Steps:
Designed a custom input architecture allowing parents to record/upload voice samples, select targeted child age groups (1-10 years), and type custom story themes.
Formulated a core Orchestrator AI Engine (LLM Node) embedded with strict developmental filters that automatically shift text difficulty, narrative pacing (10 scenes / 90 seconds), and prompt generation styles according to child age milestones.
Separated parent narration from character dialogues to enable multi-character native voice mapping and independent LipSync processing down the pipeline.
Tied a standalone secondary node for automated background score generation (music-box/lullaby bed) with a programmed cinematic fade-out transition.
Feedback on ElevenLabs:
The new modular template interface and node connection system are incredibly powerful for creating enterprise-ready SaaS wrappers. However, the system crashes and throws loop errors when trying to pass heavy structured blocks (like a 10-scene detailed JSON) into a single node's text parameters. Having more robust error-handling or internal payload distribution would fix this.
Automated Multi-Agent AI Support & Lead Triage Pipeline
Are your high-ticket clients waiting hours for an email response? This intelligent multi-agent n8n workflow instantly screens, analyzes, and responds to customer emails in real-time, utilizing advanced RAG (Retrieval-Augmented Generation) to deliver human-like support instantly.
Project Overview:
This is an enterprise-grade AI automation system designed to eliminate manual customer support queues. Instead of simple auto-replies, it uses a multi-agent routing structure combined with a dynamic knowledge base to handle complex inquiries autonomously.
How It Works (Under the Hood):
Instant Inbound Triage: A Gmail Trigger catches incoming emails instantly, extracting raw content for processing.
AI Intent Classification: An initial OpenAI model acts as a gatekeeper, analyzing the email to determine if it is a valid customer support request or irrelevant noise.
Conditional Routing: An advanced router splits the path: non-support emails receive a polite automated Telegram update, while actual support tickets are routed to the main AI engine.
Context-Aware AI Agent: The core Customer Support Agent is equipped with an OpenAI Chat Model, conversational memory, and a custom Vector Store Tool.
Pinecone RAG Integration: The agent queries a Pinecone Vector Database (powered by OpenAI Text Embeddings) to fetch real-time, accurate company documentation and context, eliminating hallucinations.
Automated Action & Response: Once the resolution is drafted, the system automatically creates a draft in Gmail for review and sends an instant internal notification via Telegram.
Why This Wins Clients (The Value Pitch):
Zero Hallucinations: Connected to a live vector database (Pinecone) so the AI only speaks from approved company data.
Reduced Overhead: Cuts down customer support response times from hours to under 60 seconds.
Production-Ready Architecture: Designed with modern n8n AI sub-nodes, structured tools, and modular scaling capabilities.
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